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    <title>Corrigan-Gibbs, Boneh, &quot;Prio: Private, Robust, and Scalable Computation of Aggregate Statistics&quot;</title>
    <dc:date>2021-05-06T07:54:31+00:00</dc:date>
    <link>https://crypto.stanford.edu/prio/paper.pdf</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[cf. https://github.com/abetterinternet/libprio-rs 

also see comments here: https://gist.github.com/degregat/75949dbf83db3a2c9dfca712cb23bac5]]></description>
<dc:subject>dan-boneh privacy statistics research-article differential-privacy machinelearning</dc:subject>
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    <title>[2009.09440] The Significance Filter, the Winner's Curse and the Need to Shrink</title>
    <dc:date>2021-05-06T07:46:50+00:00</dc:date>
    <link>https://arxiv.org/abs/2009.09440</link>
    <dc:creator>arthegall</dc:creator><dc:subject>research-article arxiv statistics bias</dc:subject>
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    <title>Anders Sandberg on Twitter: &quot;I see this paper as part of a trilogy started with our &quot;anthropic shadows&quot; paper https://t.co/82n1i1JolN and completed by a paper on observer selection effects in nuclear war near misses (coming, I promise!) Oh, and there is o</title>
    <dc:date>2020-11-25T10:05:39+00:00</dc:date>
    <link>https://twitter.com/anderssandberg/status/1331041860689780736</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA["Thread" as the kids say.  I have thoughts, but they're obvious enough that the first task would be, "read the papers in more detail to find the place where they [must be] addressed already."

https://www.nickbostrom.com/papers/anthropicshadow.pdf

Like, here's an idea: we should be able to apply this to other situations, for example, 'catastrophic security failures in tech startups.' It'd be interesting to know if the estimates lined up with prior intuition...]]></description>
<dc:subject>via:nikete anthropic-shadows observer statistics cosmology</dc:subject>
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    <title>One-step Estimators and Pathwise Derivatives / Herb Susmann / Observable</title>
    <dc:date>2020-10-16T12:30:16+00:00</dc:date>
    <link>https://observablehq.com/@herbps10/one-step-estimators-and-pathwise-derivatives</link>
    <dc:creator>arthegall</dc:creator><dc:subject>estimation statistics notebook influence-functions tutorial</dc:subject>
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    <title>Counting rare things is hard « Stats Chat</title>
    <dc:date>2020-09-28T14:53:07+00:00</dc:date>
    <link>https://www.statschat.org.nz/2020/04/19/counting-rare-things-is-hard/</link>
    <dc:creator>arthegall</dc:creator><dc:subject>statistics counting covid-19</dc:subject>
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    <title>Choi et al. &quot;Differentially-Private Multi-Party Sketching for Large-Scale Statistics&quot;</title>
    <dc:date>2020-08-01T09:41:55+00:00</dc:date>
    <link>https://petsymposium.org/2020/files/papers/issue3/popets-2020-0047.pdf</link>
    <dc:creator>arthegall</dc:creator><dc:subject>sketches probabilistic-methods differential-privacy research-article multiparty-computation statistics</dc:subject>
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    <title>The Effects of Confounding When Making Automatic Intervention Decisions Using Machine Learning by Carlos Fernández, Foster Provost :: SSRN</title>
    <dc:date>2019-12-13T10:59:45+00:00</dc:date>
    <link>https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3444678</link>
    <dc:creator>arthegall</dc:creator><dc:subject>via:arsyed confounding statistics machinelearning causality research-article ssrn sigma</dc:subject>
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    <title>[1510.05569] Estimating the Causal Impact of Recommendation Systems from Observational Data</title>
    <dc:date>2019-12-10T14:43:49+00:00</dc:date>
    <link>https://arxiv.org/abs/1510.05569</link>
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    <title>[1511.05219] How much does your data exploration overfit? Controlling bias via information usage</title>
    <dc:date>2019-10-12T09:41:21+00:00</dc:date>
    <link>https://arxiv.org/abs/1511.05219</link>
    <dc:creator>arthegall</dc:creator><dc:subject>statistics machinelearning via:cshalizi overfitting bias arxiv research-article garden-of-forking-paths</dc:subject>
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    <title>[1909.13649] PlanAlyzer: Assessing Threats to the Validity of Online Experiments</title>
    <dc:date>2019-10-09T12:13:30+00:00</dc:date>
    <link>https://arxiv.org/abs/1909.13649</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA["We present the first approach for statically checking the internal validity of online experiments. Our checks are based on well-known problems that arise in experimental design and causal inference. Our analyses target PlanOut, a widely deployed, open-source experimentation framework that uses a domain-specific language to specify and run complex experiments. We have built a tool, PlanAlyzer, that checks PlanOut programs for a variety of threats to internal validity, including failures of randomization, treatment assignment, and causal sufficiency. PlanAlyzer uses its analyses to automatically generate *contrasts*, a key type of information required to perform valid statistical analyses over experimental results."

-- of interest for reasons of "static analysis," and experimental design]]></description>
<dc:subject>static-analysis arxiv social-science via:dean-eckles research-article internal-validity statistics experimental-design</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
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<item rdf:about="https://www.pnas.org/content/116/32/15849">
    <title>Reconciling modern machine-learning practice and the classical bias–variance trade-off | PNAS</title>
    <dc:date>2019-09-14T15:12:46+00:00</dc:date>
    <link>https://www.pnas.org/content/116/32/15849</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[Is this "to-be-shot-after-a-fair-trial?" Inquiring minds want to know]]></description>
<dc:subject>hmmm statistics machinelearning review-article bias-variance pnas</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:a4cb726efcb4/</dc:identifier>
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<item rdf:about="https://arxiv.org/abs/1905.13229">
    <title>[1905.13229] Private Hypothesis Selection</title>
    <dc:date>2019-09-06T09:24:46+00:00</dc:date>
    <link>https://arxiv.org/abs/1905.13229</link>
    <dc:creator>arthegall</dc:creator><dc:subject>differential-privacy statistics inference research-article arxiv</dc:subject>
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	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:inference"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:arxiv"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/1706.04692">
    <title>[1706.04692] Bias and high-dimensional adjustment in observational studies of peer effects</title>
    <dc:date>2019-07-31T02:44:09+00:00</dc:date>
    <link>https://arxiv.org/abs/1706.04692</link>
    <dc:creator>arthegall</dc:creator><dc:subject>dean-eckles machinelearning observational-studies via:twitter statistics arxiv research-article privacy</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:6a1f2d44e112/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:dean-eckles"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:machinelearning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:observational-studies"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:via:twitter"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:arxiv"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:privacy"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/1902.10286">
    <title>[1902.10286] On Multi-Cause Causal Inference with Unobserved Confounding: Counterexamples, Impossibility, and Alternatives</title>
    <dc:date>2019-03-12T06:54:58+00:00</dc:date>
    <link>https://arxiv.org/abs/1902.10286</link>
    <dc:creator>arthegall</dc:creator><dc:subject>via:nikete causality arxiv research-article statistics inference</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:09c9259c749b/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:via:nikete"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:causality"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:arxiv"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:inference"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://tspace.library.utoronto.ca/bitstream/1807/80786/3/Veitch_Victor_201711_PhD_thesis.pdf">
    <title>Victor Veitch, &quot;(Sparse) Exchangeable Random Graphs&quot; (phd dissertation)</title>
    <dc:date>2019-02-20T11:11:07+00:00</dc:date>
    <link>https://tspace.library.utoronto.ca/bitstream/1807/80786/3/Veitch_Victor_201711_PhD_thesis.pdf</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[(One of Daniel Roy's students) 


"This thesis develops the statistical theory for network valued data; in particular, generalizing the dense exchangeable models to the sparse graph regime. The key ingredient is a novel notion of exchangeability for graphs based on a point process representation of networks. The main results are: The construction of a new modeling framework through a de Finetti style representation theorem. The characterization of several important sampling distribution properties of the resulting random graphs. The introduction of a generic non-parametric estimator (analogous to the empirical
measure) for these models"]]></description>
<dc:subject>dissertation daniel-roy random-graphs statistics graph-theory</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:3a80d89690b3/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:dissertation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:daniel-roy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:random-graphs"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:graph-theory"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://ideas.repec.org/p/iza/izadps/dp11796.html">
    <title>Methods Matter: P-Hacking and Causal Inference in Economics</title>
    <dc:date>2018-09-20T09:57:22+00:00</dc:date>
    <link>https://ideas.repec.org/p/iza/izadps/dp11796.html</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[spoiler alert: IV methods do not come out looking great]]></description>
<dc:subject>instrumental-variable p-hacking economics statistics research-article statistical-significance</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:cbeba9702364/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:instrumental-variable"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:p-hacking"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:economics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistical-significance"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://projecteuclid.org/euclid.bsmsp">
    <title>Berkeley Symposium on Mathematical Statistics and Probability (Project Euclid)</title>
    <dc:date>2018-05-04T10:38:27+00:00</dc:date>
    <link>https://projecteuclid.org/euclid.bsmsp</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[Dated, but tons of historically amazing stuff in these six symposia.]]></description>
<dc:subject>history statistics publications research-articles</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:0f1e15bb1dee/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:history"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:publications"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-articles"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://www.carolineuhler.com/publications">
    <title>Publications | MIT | Caroline Uhler</title>
    <dc:date>2018-04-23T18:36:07+00:00</dc:date>
    <link>https://www.carolineuhler.com/publications</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[(In particular https://arxiv.org/abs/0906.3529, https://arxiv.org/abs/1412.6185, https://arxiv.org/abs/1707.04345) 
]]></description>
<dc:subject>algebraic-geometry statistics graphical-models gwas research publications bernd-sturmfels mit</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:610649227022/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:algebraic-geometry"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:graphical-models"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:gwas"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:publications"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:bernd-sturmfels"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:mit"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://projecteuclid.org/euclid.lnms/1249305323">
    <title>On the Non-Optimality of Optimal Procedures</title>
    <dc:date>2018-04-20T15:05:36+00:00</dc:date>
    <link>https://projecteuclid.org/euclid.lnms/1249305323</link>
    <dc:creator>arthegall</dc:creator><dc:subject>via:? optimization statistics research-article</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:f40b72540111/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:via:?"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:optimization"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://projecteuclid.org/euclid.aos/1176345778">
    <title>Efron : Maximum Likelihood and Decision Theory</title>
    <dc:date>2017-03-08T04:38:40+00:00</dc:date>
    <link>https://projecteuclid.org/euclid.aos/1176345778</link>
    <dc:creator>arthegall</dc:creator><dc:subject>efron statistics maximum-likelihood review-article annals-statistics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:4b3f8bd8f4bf/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:efron"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:maximum-likelihood"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:review-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:annals-statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/1504.01132">
    <title>[1504.01132] Recursive Partitioning for Heterogeneous Causal Effects</title>
    <dc:date>2016-11-30T18:52:11+00:00</dc:date>
    <link>https://arxiv.org/abs/1504.01132</link>
    <dc:creator>arthegall</dc:creator><dc:subject>guido-imbens arxiv preprint statistics causal-modeling</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:2ef2a2786ff2/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:guido-imbens"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:arxiv"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:preprint"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:causal-modeling"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://arxiv.org/abs/1511.01437">
    <title>[1511.01437] The sample size required in importance sampling</title>
    <dc:date>2016-11-03T17:29:10+00:00</dc:date>
    <link>https://arxiv.org/abs/1511.01437</link>
    <dc:creator>arthegall</dc:creator><dc:subject>persi-diaconis probability importance-sampling sampling research-article arxiv statistics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:53a2b4f4c328/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:persi-diaconis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:probability"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:importance-sampling"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:sampling"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:arxiv"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://arxiv.org/abs/1507.03652">
    <title>[1507.03652] Lasso adjustments of treatment effect estimates in randomized experiments</title>
    <dc:date>2016-08-11T10:40:23+00:00</dc:date>
    <link>http://arxiv.org/abs/1507.03652</link>
    <dc:creator>arthegall</dc:creator><dc:subject>lasso regression statistics randomized-experiments research-article arxiv</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:3b0a2bb2238b/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:lasso"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:regression"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:randomized-experiments"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:arxiv"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://blog.shakirm.com/wp-content/uploads/2015/07/SVDL.pdf">
    <title>&quot;A Statistical View of Machine Learning&quot; (Shakir Mohamed)</title>
    <dc:date>2016-08-09T10:27:10+00:00</dc:date>
    <link>http://blog.shakirm.com/wp-content/uploads/2015/07/SVDL.pdf</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[A set of notes.  I'm a little confused by the (implied) viewpoint, that "deep" == "any nonlinear, hierarchical model." ]]></description>
<dc:subject>shakir-mohamed deep-learning machinelearning statistics notes via:twitter</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:7fdfa0b662ad/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:shakir-mohamed"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:deep-learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:machinelearning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:notes"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:via:twitter"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://arxiv.org/abs/1604.03924">
    <title>[1604.03924] Max-Information, Differential Privacy, and Post-Selection Hypothesis Testing</title>
    <dc:date>2016-04-29T17:37:20+00:00</dc:date>
    <link>http://arxiv.org/abs/1604.03924</link>
    <dc:creator>arthegall</dc:creator><dc:subject>via:nikete differential-privacy hypothesis-testing statistics overfitting holdout generalization arxiv research-article machinelearning</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:81cae3f02fee/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:via:nikete"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:differential-privacy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:hypothesis-testing"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:overfitting"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:holdout"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:generalization"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:arxiv"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:machinelearning"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.mosaic-web.org/go/StatisticalModeling/">
    <title>Statistical Modeling: A Fresh Approach</title>
    <dc:date>2016-01-08T11:58:16+00:00</dc:date>
    <link>http://www.mosaic-web.org/go/StatisticalModeling/</link>
    <dc:creator>arthegall</dc:creator><dc:subject>to-buy statistics textbook via:cshalizi?</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:02cbaa19430e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:to-buy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:textbook"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:via:cshalizi?"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://projecteuclid.org/euclid.im/1089229510">
    <title>Mitzenmacher : A Brief History of Generative Models for Power Law and Lognormal Distributions</title>
    <dc:date>2016-01-06T20:19:16+00:00</dc:date>
    <link>http://projecteuclid.org/euclid.im/1089229510</link>
    <dc:creator>arthegall</dc:creator><dc:subject>michael-mitzenmacher power-laws distributions statistics history mathematics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:c7901b47325d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:michael-mitzenmacher"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:power-laws"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:distributions"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:history"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:mathematics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://cs.nyu.edu/~dsontag/papers/HalpernEtAl_amia14.pdf">
    <title>Halpern, Choi, Horng, Sontag, &quot;Using Anchors to Estimate Clinical State without Labeled Data&quot;</title>
    <dc:date>2015-10-18T18:47:07+00:00</dc:date>
    <link>http://cs.nyu.edu/~dsontag/papers/HalpernEtAl_amia14.pdf</link>
    <dc:creator>arthegall</dc:creator><dc:subject>clinical data research-article david-sontag yoni-halpern estimation statistics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:2defc131ab51/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:clinical"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:data"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:david-sontag"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:yoni-halpern"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:estimation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://arxiv.org/abs/1510.02706">
    <title>[1510.02706] Conditional Risk Minimization for Stochastic Processes</title>
    <dc:date>2015-10-18T15:48:02+00:00</dc:date>
    <link>http://arxiv.org/abs/1510.02706</link>
    <dc:creator>arthegall</dc:creator><dc:subject>via:cshalizi arxiv research-article statistics prediction probabilistic-methods</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:3b83205aba30/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:via:cshalizi"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:arxiv"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:prediction"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:probabilistic-methods"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.genomebiology.com/2015/16/1/117">
    <title>Genome Biology | Full text | &lt;it&gt;quantro&lt;/it&gt;: a data-driven approach to guide the choice of an appropriate normalization method</title>
    <dc:date>2015-08-04T17:03:23+00:00</dc:date>
    <link>http://www.genomebiology.com/2015/16/1/117</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[Data-driven microarray normalization from Rafael Irizarry]]></description>
<dc:subject>microarrays bioinformatics normalization statistics rafael-irizarry research-article genomics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:8c5a6de1b556/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:microarrays"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:bioinformatics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:normalization"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:rafael-irizarry"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:genomics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://auai.org/uai2015/proceedings/papers/62.pdf">
    <title>Bauckhage, Kersting, and Hadiji, &quot;Parameterizing the Distance Distribution of Undirected Networks&quot;</title>
    <dc:date>2015-07-15T16:57:24+00:00</dc:date>
    <link>http://auai.org/uai2015/proceedings/papers/62.pdf</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[Oh cool! I think there are actually some connections to some genomic privacy stuff here too.]]></description>
<dc:subject>privacy genomics networks statistics via:cshalizi research-article uai distances graphs paths</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:ba16e2742414/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:privacy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:genomics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:networks"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:via:cshalizi"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:uai"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:distances"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:graphs"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:paths"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.dcscience.net/Schuemie-Madigan-2012.pdf">
    <title>Schuemie et al. &quot;Interpreting observational studies: why empirical calibration is needed to correct p-values&quot; Statistics in Medicine (2012)</title>
    <dc:date>2015-07-13T11:45:12+00:00</dc:date>
    <link>http://www.dcscience.net/Schuemie-Madigan-2012.pdf</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[To send to ... someone.]]></description>
<dc:subject>via:? p-values statistics medicine observational-studies research-article</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:d8adb7708edf/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:via:?"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:p-values"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:medicine"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:observational-studies"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://projecteuclid.org/euclid.aos/1018031101">
    <title>Dawid , Sebastiani : Coherent dispersion criteria for optimal experimental design</title>
    <dc:date>2015-07-06T11:39:54+00:00</dc:date>
    <link>http://projecteuclid.org/euclid.aos/1018031101</link>
    <dc:creator>arthegall</dc:creator><dc:subject>experimental-design statistics dawid research-article open-access</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:91541ec05958/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:experimental-design"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:dawid"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:open-access"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.probabilistic-numerics.org/assets/pdf/Diaconis_1988.pdf">
    <title>Persi Diaconis, &quot;Bayesian Numerical Analysis&quot;</title>
    <dc:date>2015-06-04T03:26:15+00:00</dc:date>
    <link>http://www.probabilistic-numerics.org/assets/pdf/Diaconis_1988.pdf</link>
    <dc:creator>arthegall</dc:creator><dc:subject>quadrature gaussian-processes statistics numerical-techniques integration persi-diaconis bayesian-methods</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:60250a0afcda/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:quadrature"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:gaussian-processes"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:numerical-techniques"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:integration"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:persi-diaconis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:bayesian-methods"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://projecteuclid.org/euclid.aos/1035844977">
    <title>McCullagh : What is a statistical model?</title>
    <dc:date>2015-05-25T19:27:29+00:00</dc:date>
    <link>http://projecteuclid.org/euclid.aos/1035844977</link>
    <dc:creator>arthegall</dc:creator><dc:subject>statistics mathematics probability project-euclid</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:7a033bab33c5/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:mathematics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:probability"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:project-euclid"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.jstatsoft.org/v11/i03/paper">
    <title>Marsaglia et al. &quot;Fast Generation of Discrete Random Variables&quot;</title>
    <dc:date>2015-05-24T12:59:13+00:00</dc:date>
    <link>http://www.jstatsoft.org/v11/i03/paper</link>
    <dc:creator>arthegall</dc:creator><dc:subject>random-numbers research-article statistics mcmc algorithms george-marsaglia</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:2c181ec9b923/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:random-numbers"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:mcmc"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:algorithms"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:george-marsaglia"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://iase-web.org/documents/SERJ/SERJ8(2)_Sotos.pdf">
    <title>Sotos et al. &quot;The Transitivity Misconception of Pearson's Correlation Coefficient&quot; Statistics Education Research Journal (2009)</title>
    <dc:date>2015-05-22T03:30:22+00:00</dc:date>
    <link>http://iase-web.org/documents/SERJ/SERJ8(2)_Sotos.pdf</link>
    <dc:creator>arthegall</dc:creator><dc:subject>correlation statistics research-article pdf perception survey via:lior-pachter</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:da1ee912a8b3/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:correlation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:pdf"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:perception"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:survey"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:via:lior-pachter"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://arxiv.org/abs/1405.2350">
    <title>[1405.2350] Hypothesis testing at the extremes: fast and robust association for high-throughput data</title>
    <dc:date>2015-03-16T15:12:16+00:00</dc:date>
    <link>http://arxiv.org/abs/1405.2350</link>
    <dc:creator>arthegall</dc:creator><dc:subject>via:vaguery arxiv genomics hypothesis-testing research-article statistics generalized-linear-models</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:44d507d2795d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:via:vaguery"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:arxiv"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:genomics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:hypothesis-testing"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:generalized-linear-models"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://arxiv.org/abs/1411.2664">
    <title>[1411.2664] Preserving Statistical Validity in Adaptive Data Analysis</title>
    <dc:date>2015-01-29T13:58:56+00:00</dc:date>
    <link>http://arxiv.org/abs/1411.2664</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[Yesss... this is great. Still reading it, but this is definitely The Future.]]></description>
<dc:subject>arxiv cynthia-dwork statistics cross-validation genomics privacy differential-privacy</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:e55a48eb06f4/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:arxiv"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:cynthia-dwork"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:cross-validation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:genomics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:privacy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:differential-privacy"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://gking.harvard.edu/files/gking/files/multi.pdf">
    <title>Iacus, King, Porro, &quot;A Theory of Statistical Inference for Matching Methods in Applied Causal Research&quot;</title>
    <dc:date>2015-01-09T13:20:46+00:00</dc:date>
    <link>http://gking.harvard.edu/files/gking/files/multi.pdf</link>
    <dc:creator>arthegall</dc:creator><dc:subject>matching causality gary-king research-article statistics inference approximate-matching</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:2a9dc6e23217/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:matching"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:causality"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:gary-king"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:inference"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:approximate-matching"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://blog.thegrandlocus.com/2014/12/longest-runs-and-dna-alignments">
    <title>Longest runs and DNA alignments | The Grand Locus</title>
    <dc:date>2015-01-09T07:13:13+00:00</dc:date>
    <link>http://blog.thegrandlocus.com/2014/12/longest-runs-and-dna-alignments</link>
    <dc:creator>arthegall</dc:creator><dc:subject>alignment sequence-analysis statistics extreme-values</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:40315c67e518/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:alignment"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:sequence-analysis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:extreme-values"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://gking.harvard.edu/publications/how-coarsening-simplifies-matching-based-causal-inference-theory">
    <title>Iacus, King, Porro, &quot;A Theory of Statistical Inference for Matching Methods in Applied Causal Research&quot; (Working Paper)</title>
    <dc:date>2014-12-03T11:23:44+00:00</dc:date>
    <link>http://gking.harvard.edu/publications/how-coarsening-simplifies-matching-based-causal-inference-theory</link>
    <dc:creator>arthegall</dc:creator><dc:subject>gary-king statistics causal-inference matching research-article working-paper</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:9ee4586f6f36/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:gary-king"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:causal-inference"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:matching"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:working-paper"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://arxiv.org/abs/1410.8260">
    <title>[1410.8260] Selecting the number of principal components: estimation of the true rank of a noisy matrix</title>
    <dc:date>2014-12-03T11:21:08+00:00</dc:date>
    <link>http://arxiv.org/abs/1410.8260</link>
    <dc:creator>arthegall</dc:creator><dc:subject>arxiv research-article statistics rank linear-algebra tracy-widom pca robert-tibshirani via:cshalizi</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:ac03c4658c97/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:arxiv"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:rank"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:linear-algebra"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:tracy-widom"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:pca"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:robert-tibshirani"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:via:cshalizi"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://andrewgelman.com/2014/06/27/quantifying-luck-vs-skill-sports/">
    <title>Quantifying luck vs. skill in sports « Statistical Modeling, Causal Inference, and Social Science Statistical Modeling, Causal Inference, and Social Science</title>
    <dc:date>2014-08-25T10:25:09+00:00</dc:date>
    <link>http://andrewgelman.com/2014/06/27/quantifying-luck-vs-skill-sports/</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[With follow-up: http://andrewgelman.com/2014/08/14/luck-vs-skill-poker/]]></description>
<dc:subject>luck skill poker sports statistics andrew-gelman</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:4696e3495ba1/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:luck"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:skill"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:poker"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:sports"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:andrew-gelman"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.slate.com/articles/health_and_science/medical_examiner/2014/07/autism_and_common_genes_environment_and_mutations_are_less_important.html">
    <title>Autism and common genes: Environment and mutations are less important.</title>
    <dc:date>2014-07-22T16:24:05+00:00</dc:date>
    <link>http://www.slate.com/articles/health_and_science/medical_examiner/2014/07/autism_and_common_genes_environment_and_mutations_are_less_important.html</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[Someone please help this psych PhD: 

"Heritability represents the portion of a certain trait that can be attributed to genetics. One example of a highly heritable trait is height. In the United States, height is 80 percent heritable. This means that your genes explain 80 percent of how tall you end up—for example, the genes of a 5’1” and 5’7” couple are unlikely to produce a 6’1” child—and the other 20 percent is left up to environmental factors, such as nutrition."]]></description>
<dc:subject>psychology slate journalism statistics heritability autism cry-for-help cri-du-coeur</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:47b6f9cb628c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:psychology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:slate"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:journalism"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:heritability"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:autism"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:cry-for-help"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:cri-du-coeur"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://simplystatistics.org/2014/06/25/privacy-as-a-function-of-sample-size/">
    <title>Privacy as a function of sample size | Simply Statistics</title>
    <dc:date>2014-07-08T15:14:21+00:00</dc:date>
    <link>http://simplystatistics.org/2014/06/25/privacy-as-a-function-of-sample-size/</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[The title of this post is itself pretty much _the_ crucial insight that a lot of people (I mean, non-math non-science people, like lawyers, jurists, politicians, and the general public) are going to need to have about concepts like "privacy" in the next 10-20 years.]]></description>
<dc:subject>privacy aggregation statistics policy government</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:c5b8759dde05/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:privacy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:aggregation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:policy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:government"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://wjh.harvard.edu/~jmitchel/writing/failed_science.htm">
    <title>Jason Mitchell &quot;On the emptiness of failed replications&quot;</title>
    <dc:date>2014-07-07T14:23:55+00:00</dc:date>
    <link>http://wjh.harvard.edu/~jmitchel/writing/failed_science.htm</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA["Recent hand-wringing over failed replications in social psychology is largely pointless, because unsuccessful experiments have no meaningful scientific value." 

Weirdly, this guy is a prof of psych at Harvard.]]></description>
<dc:subject>weird psychology statistics science replication</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:3620d691a5f0/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:weird"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:psychology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:science"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:replication"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://genomebiology.com/2011/12/4/R41">
    <title>Genome Biology | Full text | GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers</title>
    <dc:date>2014-07-04T09:41:36+00:00</dc:date>
    <link>http://genomebiology.com/2011/12/4/R41</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[The GISTIC2.0 paper ]]></description>
<dc:subject>gistic cancer genomics research-article work statistics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:f2f5d89e1b79/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:gistic"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:cancer"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:genomics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:work"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://europepmc.org/abstract/MED/24336643">
    <title>BETASEQ: a powerful novel method to control type-I error inflation in partially sequenced data... - Abstract - Europe PubMed Central</title>
    <dc:date>2014-07-03T16:00:47+00:00</dc:date>
    <link>http://europepmc.org/abstract/MED/24336643</link>
    <dc:creator>arthegall</dc:creator><dc:subject>research-article association-testing genetics statistics work</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:f05f0a6ce792/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:association-testing"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:genetics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:work"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://andrewgelman.com/2014/06/18/jeremy-freese-adds-new-item-lexicon/">
    <title>&quot;Statistical chemotherapy&quot;: Jeremy Freese adds a new item to the lexicon! « Statistical Modeling, Causal Inference, and Social Science Statistical Modeling, Causal Inference, and Social Science</title>
    <dc:date>2014-06-18T11:25:20+00:00</dc:date>
    <link>http://andrewgelman.com/2014/06/18/jeremy-freese-adds-new-item-lexicon/</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[Oooh, I think I missed the "more vampirical than empirical," the first time around too, both quips are great.  ]]></description>
<dc:subject>bon-mots wit statistics p-hacking andrew-gelman jeremy-freese</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:5dc2de7dc9cc/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:bon-mots"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:wit"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:p-hacking"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:andrew-gelman"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:jeremy-freese"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://scatter.wordpress.com/2014/06/03/my-thoughts-on-that-hurricane-study/">
    <title>my thoughts on that hurricane study « scatterplot</title>
    <dc:date>2014-06-04T10:51:10+00:00</dc:date>
    <link>http://scatter.wordpress.com/2014/06/03/my-thoughts-on-that-hurricane-study/</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA["Regarding overall sophistication, to give a simple example, it might seem obvious that an explanatory variable like the dollar value of hurricane damage would fit better if it was logged. A few seconds of work confirms this intuition, but it is unclear whether or how much probing like this was done by the authors." 

Ouch. I mean, the whole thing is "ouch," but that line especially.

This paper seems like a prime candidate to have links to this unpublished thing: 
http://www.stat.columbia.edu/~gelman/research/unpublished/p_hacking.pdf
plastered across the top of every page.  ]]></description>
<dc:subject>p-hacking hurricanes refutation statistics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:db2a1af9889b/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:p-hacking"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:hurricanes"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:refutation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.lse.ac.uk/statistics/news/ObituaryJamesDurbin.pdf">
    <title>Obituary for James Durbin</title>
    <dc:date>2014-05-19T10:44:59+00:00</dc:date>
    <link>http://www.lse.ac.uk/statistics/news/ObituaryJamesDurbin.pdf</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[Ah, Jim Durbin was Richard Durbin's father.]]></description>
<dc:subject>richard-durbin statistics history work genetics obituary</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:ae085c8fdcea/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:richard-durbin"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:history"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:work"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:genetics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:obituary"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://arxiv.org/abs/1404.7530">
    <title>[1404.7530] Design and analysis of experiments in networks: Reducing bias from interference</title>
    <dc:date>2014-05-02T02:11:51+00:00</dc:date>
    <link>http://arxiv.org/abs/1404.7530</link>
    <dc:creator>arthegall</dc:creator><dc:subject>networks estimation statistics arxiv research-article via:?</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:2a33be44e077/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:networks"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:estimation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:arxiv"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:via:?"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://github.com/dmbates/MixedModels.jl">
    <title>dmbates/MixedModels.jl</title>
    <dc:date>2013-12-10T10:54:45+00:00</dc:date>
    <link>https://github.com/dmbates/MixedModels.jl</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[Oooh.... my interest in Julia just jumped 75%.]]></description>
<dc:subject>julia douglas-bates mixed-effects-models statistics code github opensource</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:56d284fedde6/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:julia"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:douglas-bates"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:mixed-effects-models"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:code"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:github"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:opensource"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://arxiv.org/abs/1311.4780.pdf">
    <title>[1311.4780] Asymptotically Exact, Embarrassingly Parallel MCMC</title>
    <dc:date>2013-12-06T10:40:23+00:00</dc:date>
    <link>http://arxiv.org/abs/1311.4780.pdf</link>
    <dc:creator>arthegall</dc:creator><dc:subject>eric-xing markov-chain mcmc sampling arxiv research-article statistics parallel-computing</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:60f0ca5703be/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:eric-xing"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:markov-chain"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:mcmc"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:sampling"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:arxiv"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:parallel-computing"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://probmods.org/">
    <title>Probabilistic Models of Cognition</title>
    <dc:date>2013-11-15T13:59:16+00:00</dc:date>
    <link>https://probmods.org/</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[An online book by Noah Goodman and Josh Tenenbaum.]]></description>
<dc:subject>noah-goodman josh-tenenbaum cognition probability church statistics programminglanguages book</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:84527da8fdd0/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:noah-goodman"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:josh-tenenbaum"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:cognition"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:probability"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:church"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:programminglanguages"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:book"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.gregorypark.org/?p=359">
    <title>Kaggle Post-Mortem: Psychopathy Prediction Blowout | Gregory Park</title>
    <dc:date>2013-11-15T10:17:10+00:00</dc:date>
    <link>http://www.gregorypark.org/?p=359</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[The perils of (unintentional) overfitting.  ]]></description>
<dc:subject>machinelearning kaggle overfitting statistics example</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:743979ab35d8/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:machinelearning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:kaggle"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:overfitting"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:example"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.biomedcentral.com/1471-2105/12/290">
    <title>BMC Bioinformatics | Full text | Bias Detection and Correction in RNA-Sequencing Data</title>
    <dc:date>2013-11-03T13:42:10+00:00</dc:date>
    <link>http://www.biomedcentral.com/1471-2105/12/290</link>
    <dc:creator>arthegall</dc:creator><dc:subject>bioinformatics rna-seq research-article statistics bias</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:4ba2899e417d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:bioinformatics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:rna-seq"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:bias"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.heinz.cmu.edu/research/483full.pdf">
    <title>Flaxman, Neill, Smola, &quot;Correlates of homicide: new space/time interaction tests for spatiotemporal point processes&quot;</title>
    <dc:date>2013-11-03T13:00:03+00:00</dc:date>
    <link>http://www.heinz.cmu.edu/research/483full.pdf</link>
    <dc:creator>arthegall</dc:creator><dc:subject>poisson-processes research-article social-science alex-smola crime-data homicides statistics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:f2c929b4fd17/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:poisson-processes"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:social-science"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:alex-smola"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:crime-data"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:homicides"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://andrewgelman.com/2013/10/27/uncompressing-the-concept-of-compressed-sensing/">
    <title>Uncompressing the concept of compressed sensing « Statistical Modeling, Causal Inference, and Social Science Statistical Modeling, Causal Inference, and Social Science</title>
    <dc:date>2013-10-27T13:31:28+00:00</dc:date>
    <link>http://andrewgelman.com/2013/10/27/uncompressing-the-concept-of-compressed-sensing/</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA["Meh. They proved L1 approximates L0 when design matrix is basically full rank. Now all sparsity stuff is sometimes called ‘compressed sensing’. Most of it seems to be linear interpolation, rebranded."]]></description>
<dc:subject>compressed-sensing andrew-gelman statistics funny</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:c3a667715fe6/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:compressed-sensing"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:andrew-gelman"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:funny"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://geomblog.blogspot.com/2013/09/statistics-geometry-and-computer-science.html?spref=tw">
    <title>The Geomblog: Statistics, geometry and computer science.</title>
    <dc:date>2013-09-29T19:32:12+00:00</dc:date>
    <link>http://geomblog.blogspot.com/2013/09/statistics-geometry-and-computer-science.html?spref=tw</link>
    <dc:creator>arthegall</dc:creator><dc:subject>james-stein-estimator regression statistics geometry</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:7c2dfbd34643/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:james-stein-estimator"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:regression"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:geometry"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://arxiv.org/abs/1309.0911">
    <title>[1309.0911] A Bayesian information criterion for singular models</title>
    <dc:date>2013-09-29T14:24:27+00:00</dc:date>
    <link>http://arxiv.org/abs/1309.0911</link>
    <dc:creator>arthegall</dc:creator><dc:subject>bayesian-methods arxiv research-article bic statistics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:041608cd1c80/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:bayesian-methods"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:arxiv"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:bic"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://liorpachter.wordpress.com/">
    <title>Bits of DNA | Reviews and commentary on computational biology</title>
    <dc:date>2013-09-27T09:53:17+00:00</dc:date>
    <link>http://liorpachter.wordpress.com/</link>
    <dc:creator>arthegall</dc:creator><description><![CDATA[Lior Pachter is blogging.]]></description>
<dc:subject>genomics lior-pachter statistics blog</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:77a19070677f/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:genomics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:lior-pachter"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:blog"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://arxiv.org/abs/1309.4286">
    <title>[1309.4286] Accurate Computation of Survival Statistics in Genome-wide Studies</title>
    <dc:date>2013-09-24T19:01:44+00:00</dc:date>
    <link>http://arxiv.org/abs/1309.4286</link>
    <dc:creator>arthegall</dc:creator><dc:subject>via:vaguary gwas statistics arxiv research-article survival-statistics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:f0004d5f1a33/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:via:vaguary"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:gwas"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:arxiv"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:research-article"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:survival-statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://genome.cshlp.org/content/early/2013/07/16/gr.154831.113.abstract.html">
    <title>Bhatia, Patterson, et al. &quot;Estimating and interpreting Fst: the impact of rare variants&quot; Genome Research (2013)</title>
    <dc:date>2013-09-09T18:33:45+00:00</dc:date>
    <link>http://genome.cshlp.org/content/early/2013/07/16/gr.154831.113.abstract.html</link>
    <dc:creator>arthegall</dc:creator><dc:subject>nick-patterson f_st genetics sewall-wright statistics estimation work population-genetics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:arthegall/b:a129c1850f2e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:nick-patterson"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:f_st"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:genetics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:sewall-wright"/>
	<rdf:li rdf:resource="https://pinboard.in/u:arthegall/t:statistics"/>
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