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Orange is packed with different visualizations, from scatterplots, bar charts, trees, to dendrograms, networks and heatmaps.

Actions seamlessly propagate through data analysis schema. Selection of data subset in one widget can automatically trigger change of display in the other one. By combining various widgets you can design data analytics framework of choice.

Over 100 widgets and growing. Coverage of most of standard data analysis tasks. Also specialized add-ons are available, like Bioorange for bioinformatics.

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	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:c++"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:bayes"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://code.google.com/p/factorie/">
    <title>factorie - Probabilistic programming with imperatively-defined factor graphs - Google Project Hosting</title>
    <dc:date>2012-01-23T04:22:55+00:00</dc:date>
    <link>http://code.google.com/p/factorie/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[FACTORIE is a toolkit for deployable probabilistic modeling, implemented as a software library in Scala. It provides its users with a succinct language for creating relational factor graphs, estimating parameters and performing inference. 
It is object-oriented... in the definition of random variables, factors, inference and learning methods.
It is scalable, with demonstrated success on problems with many millions of variables and factors, and on models that have changing structure, such as case factor diagrams... capable of handling billions of variables.
It is flexible, supporting multiple modeling and inference paradigms. Its original emphasis was on conditional random fields, undirected graphical models, MCMC inference, online training, and discriminative parameter estimation... has preliminary support for variational inference, including belief propagation and mean-field methods.]]></description>
<dc:subject>monte_carlo datamining statistics scala nlp</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:2ad4abc138f9/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:monte_carlo"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:scala"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:nlp"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.clips.ua.ac.be/pages/pattern">
    <title>Pattern | CLiPS</title>
    <dc:date>2012-01-23T04:15:29+00:00</dc:date>
    <link>http://www.clips.ua.ac.be/pages/pattern</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[combo data-mining/NLP/web-scraping toolkit for instant natural experiments online]]></description>
<dc:subject>api statistics nlp datamining python</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:0b2db27fe1c2/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:api"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:nlp"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://statsmodels.sourceforge.net/">
    <title>StatsModels: Statistics in Python — statsmodels v0.3.1 documentation</title>
    <dc:date>2012-01-09T05:28:39+00:00</dc:date>
    <link>http://statsmodels.sourceforge.net/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[you don't have to leave python to R for nearly as much these days.]]></description>
<dc:subject>scipy statistics python</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:668fcbd81f57/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:scipy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://ugcs.caltech.edu/~srbecker/wiki/Main_Page">
    <title>Sparse- and low-rank approximation wiki - Sparse Solver Wiki</title>
    <dc:date>2012-01-02T20:01:29+00:00</dc:date>
    <link>http://ugcs.caltech.edu/~srbecker/wiki/Main_Page</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[This wiki has information on solvers and problems that arise in these fields (and subfields, such as compressed sensing).
Everyone is welcome and encouraged to edit this wiki; it runs
Contents

The contents of this wiki have been organized into categories.
Problems formulations that arise in sparse- and low-rank approximation.
Solvers that are used for solving these problems. There are many sub-categories of solvers, such as:
Convex solvers
Greedy solvers
Matrix completion solvers
and many more (all of them listed at Solvers ).
Benchmarking/Test problems for comparing algorithms
Applications (in software) of sparsity or low-rank based techniques
Hardware devices that perform compressed sensing.
...]]></description>
<dc:subject>compressed_sensing linear_algebra statistics compact_representation</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:01dfc4b1b6e6/</dc:identifier>
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	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:linear_algebra"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:compact_representation"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://statisfaction.wordpress.com/2011/12/13/create-maps-with-maptools/">
    <title>Create maps with maptools R package | Statisfaction</title>
    <dc:date>2011-12-14T10:06:45+00:00</dc:date>
    <link>http://statisfaction.wordpress.com/2011/12/13/create-maps-with-maptools/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[How to do stats on the surface of he earth with beautiful visualizations]]></description>
<dc:subject>mapping gis r statistics france</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:0faee4025fba/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:mapping"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:gis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:france"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://agf.statsolutions.eu/">
    <title>agf.statsolutions.eu</title>
    <dc:date>2011-11-25T02:01:30+00:00</dc:date>
    <link>http://agf.statsolutions.eu/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[python minority game simulation]]></description>
<dc:subject>agents statistics matlap econophysics python game_theory economics scalability</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:c42bcca559f2/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:agents"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:matlap"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:econophysics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:game_theory"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:economics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:scalability"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://radar.oreilly.com/2011/11/automated-writing-software.html">
    <title>How I automated my writing career - O'Reilly Radar</title>
    <dc:date>2011-11-21T04:02:59+00:00</dc:date>
    <link>http://radar.oreilly.com/2011/11/automated-writing-software.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[a growth industry: automating the production of journalism, books, textual content]]></description>
<dc:subject>nlp writing ai statistics journalism</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:0bf0491fca89/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:nlp"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:writing"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:ai"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:journalism"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.psych.ualberta.ca/~phurd/cruft/">
    <title>Peter L. Hurd's page of local resources</title>
    <dc:date>2011-11-02T01:00:32+00:00</dc:date>
    <link>http://www.psych.ualberta.ca/~phurd/cruft/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[weirldy relaxed academic dispensing soothing quotes:
Do not burn yourselves out. Be as I am - a reluctant enthusiast, a part-time crusader, a half-hearted fanatic. Save the other half of yourselves and your lives for pleasure and adventure. It is not enough to fight for natural land and the west; it is even more important to enjoy it. While you can. While it's still there... Enjoy yourselves, keep your brain in your head and your head firmly attached to the body, the body active and alive, and I promise you this much: I promise you this one sweet victory over our enemies, over those desk-bound men with their hearts in a safe deposit box, and their eyes hypnotized by desk calculators. I promise you this: you will outlive the bastards. --Ed Abbey.]]></description>
<dc:subject>statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:1fdceada9b60/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.voxeu.org/index.php?q=node/6158">
    <title>Forecasts performing badly: New insights on dynamic stochastic general equilibrium models | vox - Research-based policy analysis and commentary from leading economists</title>
    <dc:date>2011-10-16T13:56:36+00:00</dc:date>
    <link>http://www.voxeu.org/index.php?q=node/6158</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[If dsge performs better than the competitors, does that mean that it performs still?
]]></description>
<dc:subject>Economics Statistics Hps methodology macroeconomics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:f3196d705e25/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:Economics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:Statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:Hps"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:methodology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:macroeconomics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://a-little-book-of-r-for-time-series.readthedocs.org/en/latest/">
    <title>Welcome to a Little Book of R for Time Series! — Time Series v0.1 documentation</title>
    <dc:date>2011-09-13T07:38:53+00:00</dc:date>
    <link>http://a-little-book-of-r-for-time-series.readthedocs.org/en/latest/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[A gentle climb up a staircase, atop which is ARIMA.
]]></description>
<dc:subject>R statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:3f3f80b94580/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:R"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://wesmckinney.com/blog/?p=77">
    <title>A Roadmap for Rich Scientific Data Structures in Python | Quant Pythonista</title>
    <dc:date>2011-09-09T05:18:34+00:00</dc:date>
    <link>http://wesmckinney.com/blog/?p=77</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA["So, this post is a bit of a brain dump on rich data structures in Python and what needs to happen in the very near future. I care about them for statistical computing (I want to build a statistical computing environment that trounces R) and financial data analysis (all evidence leads me to believe that Python is the best all-around tool for the finance space). Other people in the scientific Python community want them for numerous other applications: geophysics, neuroscience, etc. It’s really hard to make everyone happy with a single solution. But the current state of affairs has me rather anxious. And I’d like to explain why..."
]]></description>
<dc:subject>statistics Python R visualisation db nosql has:for</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:a57a463047d4/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:Python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:R"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:visualisation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:db"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:nosql"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:has:for"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://pandas.sourceforge.net/index.html">
    <title>pandas: a python data analysis library — pandas v0.4.0dev documentation</title>
    <dc:date>2011-08-13T11:25:59+00:00</dc:date>
    <link>http://pandas.sourceforge.net/index.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA["pandas is a python package providing convenient data structures for time series, cross-sectional, or any other form of “labeled” data, with tools for building statistical and econometric models."

handle data in python intuitively. pass to R for fiddly bits.
]]></description>
<dc:subject>Python R metadata statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:858ee502e4c1/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:Python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:R"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:metadata"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.itl.nist.gov/div898/handbook/index.htm">
    <title>NIST/SEMATECH e-Handbook of Statistical Methods</title>
    <dc:date>2011-08-08T01:25:46+00:00</dc:date>
    <link>http://www.itl.nist.gov/div898/handbook/index.htm</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[neat alternate perspective on statistics, in that kind of living-in-a-funding-bubble US NIST kind of way. Bit of an exploratory daya analysis focus, but still worthwhile.
]]></description>
<dc:subject>statistics howto hps</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:530a40d6ad2c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:howto"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:hps"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.math.dartmouth.edu/~doyle/">
    <title>Peter Doyle</title>
    <dc:date>2011-08-05T22:03:03+00:00</dc:date>
    <link>http://www.math.dartmouth.edu/~doyle/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[a great collection of mathquirk, all online and free
]]></description>
<dc:subject>maths statistics geometry</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:09eb40f0e33c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:maths"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:geometry"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://terrytao.wordpress.com/2007/04/15/ostrowski-lecture-the-uniform-uncertainty-principle-and-compressed-sensing/">
    <title>Ostrowski lecture: The uniform uncertainty principle and compressed sensing « What’s new</title>
    <dc:date>2011-07-25T10:31:07+00:00</dc:date>
    <link>http://terrytao.wordpress.com/2007/04/15/ostrowski-lecture-the-uniform-uncertainty-principle-and-compressed-sensing/</link>
    <dc:creator>howthebodyworks</dc:creator><dc:subject>computer_vision learning statistics GRAMMARTHING grammarface compressed_sensing</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:07cd5a082137/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:computer_vision"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:GRAMMARTHING"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:grammarface"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:compressed_sensing"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.math.ucla.edu/~tao/preprints/sparse.html">
    <title>Compressed sensing</title>
    <dc:date>2011-07-25T10:26:23+00:00</dc:date>
    <link>http://www.math.ucla.edu/~tao/preprints/sparse.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[The uniform uncertainty principle and compressed sensing
]]></description>
<dc:subject>computer_vision learning statistics GRAMMARTHING grammarface compressed_sensing</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:c783c3afb6bd/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:computer_vision"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:GRAMMARTHING"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:grammarface"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:compressed_sensing"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://practicalquant.blogspot.com/2010/10/compressed-sensing-and-big-data.html">
    <title>The Practical Quant: Compressed Sensing and Big Data</title>
    <dc:date>2011-07-25T10:21:45+00:00</dc:date>
    <link>http://practicalquant.blogspot.com/2010/10/compressed-sensing-and-big-data.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[Best explanation of this sparse image representation thing that I have yet seen. Well wicked.
]]></description>
<dc:subject>computer_vision learning statistics GRAMMARTHING grammarface compressed_sensing</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:0defc5693cf2/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:computer_vision"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:GRAMMARTHING"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:grammarface"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:compressed_sensing"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://uncertainty.stat.cmu.edu/">
    <title>Principles of Uncertainty | Statistics, Mathematics, Philosophy</title>
    <dc:date>2011-06-14T11:26:19+00:00</dc:date>
    <link>http://uncertainty.stat.cmu.edu/</link>
    <dc:creator>howthebodyworks</dc:creator><dc:subject>pdf ebook statistics reference</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:87278d04d8f8/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:pdf"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:ebook"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:reference"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://exploringdatablog.blogspot.com/2011/04/interestingness-measures.html">
    <title>ExploringDataBlog: Interestingness Measures</title>
    <dc:date>2011-05-30T02:27:14+00:00</dc:date>
    <link>http://exploringdatablog.blogspot.com/2011/04/interestingness-measures.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[categorical data has other Shannon-information-like estiamtors of "interestingness"
]]></description>
<dc:subject>statistics r information_theory bubble_economy</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:c4557570196c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:information_theory"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:bubble_economy"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://networkx.lanl.gov/">
    <title>Overview — NetworkX v1.4 documentation</title>
    <dc:date>2011-05-30T02:19:15+00:00</dc:date>
    <link>http://networkx.lanl.gov/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[native python graph handling with ultralight api built aroudn hashes.
]]></description>
<dc:subject>python networks statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:5dcfb552364e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:networks"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://igraph.sourceforge.net/index.html">
    <title>The igraph library for complex network research</title>
    <dc:date>2011-05-30T02:18:27+00:00</dc:date>
    <link>http://igraph.sourceforge.net/index.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[c graph library with r and python support
]]></description>
<dc:subject>networks r python statistics c</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:9224124df217/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:networks"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:c"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://projects.skewed.de/graph-tool/">
    <title>graph-tool</title>
    <dc:date>2011-05-30T02:17:06+00:00</dc:date>
    <link>http://projects.skewed.de/graph-tool/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[c++ graph lib for python, optimised for performance.
]]></description>
<dc:subject>python networks c++ boost statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:98e2befeed5c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:networks"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:c++"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:boost"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://onlineprediction.net/?n=Main.On-linePrediction">
    <title>on-line prediction wiki - On-line Prediction</title>
    <dc:date>2011-04-06T07:16:34+00:00</dc:date>
    <link>http://onlineprediction.net/?n=Main.On-linePrediction</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[Prediction as a game against nature. Weird science.
]]></description>
<dc:subject>statistics methodology hps gametheory</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:55e74642f6a5/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:methodology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:hps"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:gametheory"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://gael-varoquaux.info/blog/?p=143">
    <title>Gaël Varoquaux » Blog Archive » ICA versus PCA in the scikit-learn: the value of code over pictures</title>
    <dc:date>2011-04-06T06:55:25+00:00</dc:date>
    <link>http://gael-varoquaux.info/blog/?p=143</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[depicting PCA versus ICA using scipy
]]></description>
<dc:subject>visualization python pca ica linear_algebra scipy statistics howto</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:a4aa948a2c03/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:visualization"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:pca"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:ica"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:linear_algebra"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:scipy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:howto"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.mtm.ufsc.br/~taneja/book/book.html">
    <title>Generalized Information Measures and Their Applications</title>
    <dc:date>2011-04-06T03:26:03+00:00</dc:date>
    <link>http://www.mtm.ufsc.br/~taneja/book/book.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[TANEJA. I.J. (2001), - this has the stuff about norms and maximum entropy measures etc and their implications
]]></description>
<dc:subject>information_theory statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:22f72f915b09/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:information_theory"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.stat.columbia.edu/~cook/movabletype/archives/2006/11/bayesian_infere_3.html">
    <title>Bayesian inference of the median - Statistical Modeling, Causal Inference, and Social Science</title>
    <dc:date>2011-04-06T03:09:43+00:00</dc:date>
    <link>http://www.stat.columbia.edu/~cook/movabletype/archives/2006/11/bayesian_infere_3.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA["In that sense, when people play with loss functions, they are essentially also playing with probability distributions that are entailed by the loss functions. When they use L1 or L2 regularization for regression, they are picking either Gaussian or Laplace priors for the parameters. The reason for the popularity has been primarily the realization that Laplace prior is better than Gaussian prior on many benchmarks. I wonder if the log(1+d^2) norms will generate as many papers as L1, or whether statisticians will migrate from Student to Laplace."
]]></description>
<dc:subject>bayes statistics maxent</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:819e1e876bc9/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:bayes"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:maxent"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://mdp-toolkit.sourceforge.net/">
    <title>Homepage — Modular toolkit for Data Processing (MDP)</title>
    <dc:date>2011-03-25T12:47:04+00:00</dc:date>
    <link>http://mdp-toolkit.sourceforge.net/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[sweet looking machine learning toolchain for python
]]></description>
<dc:subject>python statistics ai</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:6d365a6a44fc/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:ai"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.greenteapress.com/thinkstats/">
    <title>Think Stats: Probability and Statistics for Programmers</title>
    <dc:date>2011-03-21T12:16:21+00:00</dc:date>
    <link>http://www.greenteapress.com/thinkstats/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[hawt python statistics. If you don't actually like R THAT much.
]]></description>
<dc:subject>python statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:cbc52a42ff96/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://madlib.net/">
    <title>MADlib</title>
    <dc:date>2011-03-15T07:22:18+00:00</dc:date>
    <link>http://madlib.net/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[statiscial analysis on your database contents:  "MADlib is an open-source library for scalable in-database analytics. It provides data-parallel implementations of mathematical, statistical and machine learning methods for structured and unstructured data". Seems to be largely in PL/C, with some bonus python on the front.
]]></description>
<dc:subject>python statistics postgresql sql db greenplum mapreduce ai classification</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:6113a7417356/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:postgresql"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:sql"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:db"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:greenplum"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:mapreduce"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:ai"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:classification"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://connectmv.com/tutorials/r-tutorial/">
    <title>ConnectMV | Process Improvement using Data</title>
    <dc:date>2011-03-09T04:53:01+00:00</dc:date>
    <link>http://connectmv.com/tutorials/r-tutorial/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[interesting bunch of courses on statistical data fiddling
]]></description>
<dc:subject>r howto statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:f65ec9689d96/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:howto"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.burns-stat.com/pages/Tutor/hints_R_begin.html#langs">
    <title>Burns Statistics -- Some Hints for the R Beginner</title>
    <dc:date>2011-01-25T13:08:59+00:00</dc:date>
    <link>http://www.burns-stat.com/pages/Tutor/hints_R_begin.html#langs</link>
    <dc:creator>howthebodyworks</dc:creator><dc:subject>r statistics howto</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:72be37f8b5f8/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:howto"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://understandinguncertainty.org/">
    <title>Understanding Uncertainty</title>
    <dc:date>2011-01-21T09:32:29+00:00</dc:date>
    <link>http://understandinguncertainty.org/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[science communication expert explains probability with rare precision. excellent for tips about communicating risk and lots of tasty examples (comparing hose riding with ecstasy, motorbikes with pregnancy, all that stuff)
]]></description>
<dc:subject>risk crisis statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:ce627b83a03e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:risk"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:crisis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://gist.github.com/757090">
    <title>gist: 757090 - Comparison of MCMC implementations in Python and Cython. This is discussed here: http://pyinsci.blogspot.com/2010/12/efficcient-mcmc-in-python.html- GitHub</title>
    <dc:date>2011-01-19T11:32:07+00:00</dc:date>
    <link>https://gist.github.com/757090</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[handy performance tip example -wrap gsl library calls in cython
]]></description>
<dc:subject>performance python monte_carlo statistics cython</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:fbe1ceee510a/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:performance"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:monte_carlo"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:cython"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://pyinsci.blogspot.com/2010/12/efficcient-mcmc-in-python.html?utm_source=feedburner&amp;utm_medium=feed&amp;utm_campaign=Feed%3A+PythonInScience+(Python+in+Science)">
    <title>Python in Science: Efficcient MCMC in Python</title>
    <dc:date>2010-12-27T07:30:45+00:00</dc:date>
    <link>http://pyinsci.blogspot.com/2010/12/efficcient-mcmc-in-python.html?utm_source=feedburner&amp;utm_medium=feed&amp;utm_campaign=Feed%3A+PythonInScience+(Python+in+Science)</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[optimising crazy inner loops in cython using GSL calls.
]]></description>
<dc:subject>python performance monte_carlo statistics cython</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:b5289dd11090/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:performance"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:monte_carlo"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:cython"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://rb-gsl.rubyforge.org/">
    <title>Ruby/GSL</title>
    <dc:date>2010-12-18T23:32:44+00:00</dc:date>
    <link>http://rb-gsl.rubyforge.org/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[Rubt's sparse but serviceable answer to numpy
]]></description>
<dc:subject>gnu science linear_algebra statistics ruby mathematics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:e689eb6ba6dd/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:gnu"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:science"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:linear_algebra"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:ruby"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:mathematics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.decisionsciencenews.com/2010/12/03/some-ideas-on-communicating-risks-to-the-general-public/">
    <title>SOME IDEAS ON COMMUNICATING RISK TO THE GENERAL PUBLIC | Decision Science News</title>
    <dc:date>2010-12-08T06:03:35+00:00</dc:date>
    <link>http://www.decisionsciencenews.com/2010/12/03/some-ideas-on-communicating-risks-to-the-general-public/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[not pretty, but necessary. How to comunicate statistics and risks to people in a matter which suffers least at the hands of our inherent cognitive biases
]]></description>
<dc:subject>visualization risk mind crisis statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:1867fd802ebd/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:visualization"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:risk"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:mind"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:crisis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://intersci.ss.uci.edu/wiki/index.php/InterSciWiki:Community_Portal">
    <title>InterSciWiki:Community Portal - InterSciWiki</title>
    <dc:date>2010-11-29T06:21:13+00:00</dc:date>
    <link>http://intersci.ss.uci.edu/wiki/index.php/InterSciWiki:Community_Portal</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[interesting little wiki of complexity and emergence for the student-type.
]]></description>
<dc:subject>transdisciplinary complexity statistics methodology networks wiki</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:7e43afbac517/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:transdisciplinary"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:complexity"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:methodology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:networks"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:wiki"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://xianblog.wordpress.com/2010/09/13/simply-start-over-and-build-something-better/">
    <title>“simply start over and build something better” « Xi'an's Og</title>
    <dc:date>2010-11-29T05:23:11+00:00</dc:date>
    <link>http://xianblog.wordpress.com/2010/09/13/simply-start-over-and-build-something-better/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[the case for replacing the language of R with somethig else that can access the same statistical power
]]></description>
<dc:subject>r statistics compsci coding</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:0e6f3992be9f/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:compsci"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:coding"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://bactra.org/weblog/698.html">
    <title>The Neutral Model of Inquiry (or, What Is the Scientific Literature, Chopped Liver?)</title>
    <dc:date>2010-11-16T08:19:09+00:00</dc:date>
    <link>http://bactra.org/weblog/698.html</link>
    <dc:creator>howthebodyworks</dc:creator><dc:subject>hps methodology statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:22fb22fd80b7/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:hps"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:methodology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://tuvalu.santafe.edu/~aaronc/powerlaws/">
    <title>Power-law Distributions</title>
    <dc:date>2010-11-11T02:03:01+00:00</dc:date>
    <link>http://tuvalu.santafe.edu/~aaronc/powerlaws/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[how to find, in a statistically valid fashion, that your data fits a power law.
]]></description>
<dc:subject>statistics scaling powerlaw matlab python r</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:9021519cd0c6/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:scaling"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:powerlaw"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:matlab"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://controls.engin.umich.edu/wiki/index.php/Correlation_and_Mutual_Information">
    <title>Correlation and Mutual Information - ControlsWiki</title>
    <dc:date>2010-11-02T01:06:09+00:00</dc:date>
    <link>http://controls.engin.umich.edu/wiki/index.php/Correlation_and_Mutual_Information</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[best explanation of mutual_information on the interweb,
]]></description>
<dc:subject>statistics mutual_information</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:1a927bc7c28d/</dc:identifier>
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</item>
<item rdf:about="http://www.slideshare.net/xianblog/mcmc-and-likelihoodfree-methods?from=fblanding">
    <title>MCMC and likelihood-free methods</title>
    <dc:date>2010-11-01T04:55:57+00:00</dc:date>
    <link>http://www.slideshare.net/xianblog/mcmc-and-likelihoodfree-methods?from=fblanding</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[MCMC, Monte Carlo methods, and the Metropolis -Hastings sampling doohickey for fun and profit. Well, profit.
]]></description>
<dc:subject>statistics numerical_methods methodology</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:5f9c7a15e86e/</dc:identifier>
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	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:methodology"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://code.google.com/p/pymc/">
    <title>pymc - Project Hosting on Google Code</title>
    <dc:date>2010-10-29T23:32:52+00:00</dc:date>
    <link>http://code.google.com/p/pymc/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[Bayesian estimation, particularly using Markov chain Monte Carlo (MCMC), is an increasingly relevant approach to statistical estimation. However, few statistical software packages implement MCMC samplers, and they are non-trivial to code by hand. PyMC is a python module that implements the Metropolis-Hastings algorithm as a python class, and is extremely flexible and applicable to a large suite of problems. PyMC includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics
]]></description>
<dc:subject>monte_carlo python statistics bayes datamining markov modelling</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:a0e2ecfb76de/</dc:identifier>
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</item>
<item rdf:about="http://www.fizyka.umk.pl/nrbook/bookcpdf.html">
    <title>Numerical Recipes in C</title>
    <dc:date>2010-10-29T23:15:13+00:00</dc:date>
    <link>http://www.fizyka.umk.pl/nrbook/bookcpdf.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[numerical recipes in c, 2nd edition, is online.
]]></description>
<dc:subject>compsci c algorithm programming simulation statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:55eb7c588642/</dc:identifier>
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</item>
<item rdf:about="http://psoup.math.wisc.edu/welcome.html">
    <title>Come on in my kitchen ...</title>
    <dc:date>2010-10-28T05:30:13+00:00</dc:date>
    <link>http://psoup.math.wisc.edu/welcome.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[the statistics and evolution of interesting random cellular automata
]]></description>
<dc:subject>cellularautomata statistics evolution</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:42b8a0812b8f/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:cellularautomata"/>
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	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:evolution"/>
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</item>
<item rdf:about="http://stats.stackexchange.com/">
    <title>Statistical Analysis - Stack Exchange</title>
    <dc:date>2010-10-27T05:08:13+00:00</dc:date>
    <link>http://stats.stackexchange.com/</link>
    <dc:creator>howthebodyworks</dc:creator><dc:subject>statistics collaborative q&amp;a</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:b3a11bd4b6a4/</dc:identifier>
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	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:collaborative"/>
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</item>
<item rdf:about="http://strimmerlab.org/software/entropy/">
    <title>R: Entropy and Mutual Information Estimation</title>
    <dc:date>2010-10-25T01:02:23+00:00</dc:date>
    <link>http://strimmerlab.org/software/entropy/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[MI and H estimates
]]></description>
<dc:subject>information_theory r statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:b2b11ec94d19/</dc:identifier>
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	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
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</item>
<item rdf:about="http://code.google.com/p/pyentropy/">
    <title>pyentropy - Project Hosting on Google Code</title>
    <dc:date>2010-10-24T05:30:27+00:00</dc:date>
    <link>http://code.google.com/p/pyentropy/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[information theoretic widgets and doohickeys for python statistics
]]></description>
<dc:subject>information_theory python statistics neuron numpy academic</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:f066d73864a0/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:information_theory"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:neuron"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:numpy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:academic"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://rpy.sourceforge.net/rpy2.html">
    <title>http://rpy.sourceforge.net/rpy2.html</title>
    <dc:date>2010-10-19T00:18:24+00:00</dc:date>
    <link>http://rpy.sourceforge.net/rpy2.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[the python<->R interface is being rebooted
]]></description>
<dc:subject>r python api statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:ff72f8740594/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
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	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://had.co.nz/ggplot2/">
    <title>ggplot. had.co.nz</title>
    <dc:date>2010-10-15T00:08:49+00:00</dc:date>
    <link>http://had.co.nz/ggplot2/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[Tufte-compliant graphing tricks for R
]]></description>
<dc:subject>r visualization statistics academic parsimony</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:0e85e633fb49/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:r"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:visualization"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:academic"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:parsimony"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://code.google.com/p/bryan-code/">
    <title>bryan-code - Project Hosting on Google Code</title>
    <dc:date>2010-10-07T02:33:29+00:00</dc:date>
    <link>http://code.google.com/p/bryan-code/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[handy image processing code in python, including similarity detection, mutual information  volumetric rendering and so on
]]></description>
<dc:subject>image python numpy statistics 3d</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:e52d4c091321/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:image"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:numpy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:3d"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://ccsl.mae.cornell.edu/eureqa">
    <title>Eureqa | Cornell Computational Synthesis Laboratory</title>
    <dc:date>2010-10-04T23:26:56+00:00</dc:date>
    <link>http://ccsl.mae.cornell.edu/eureqa</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[it's the page of that  trendy work-out-your-laws-for-you package
]]></description>
<dc:subject>ai learning academic methodology datamining genetic parsimony statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:4347b90e84f5/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:ai"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:academic"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:methodology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:datamining"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:genetic"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:parsimony"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
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</item>
<item rdf:about="http://zedshaw.com/essays/programmer_stats.html">
    <title>Programmers Need To Learn Statistics Or I Will Kill Them All</title>
    <dc:date>2010-10-01T01:52:37+00:00</dc:date>
    <link>http://zedshaw.com/essays/programmer_stats.html</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[This guy is reliably entertaining. in this case, it's a userful, arrogant rant about what you need to know about stats to push beyond the "mean request time or whatever. highlights:


>The next day we had IBM fixing the problem (turned out to be a single update index command) and we all kept our jobs. That’s what a proper analysis method can do for you.

>still I see software developers begging for gazillions of dollars to buy some crap tool that doesn’t even mention “standard deviation”, but throws “user” around like it’s Dr. Phil treating Robert Downey Jr. for heroin addiction.
]]></description>
<dc:subject>r reference statistics performance compsci dear_me</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:230efc5ec48b/</dc:identifier>
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	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:reference"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:performance"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:compsci"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:dear_me"/>
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</item>
<item rdf:about="http://www.spatialanalysisonline.com/">
    <title>Geospatial Analysis - spatial and GIS analysis techniques and GIS software</title>
    <dc:date>2010-09-28T07:29:15+00:00</dc:date>
    <link>http://www.spatialanalysisonline.com/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[online free ebook about the stats and tools needed for all that trendy geospatial shit to happen in a rigorous way
]]></description>
<dc:subject>gis howto academic ebook agents statistics</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:902ad02233af/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:gis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:howto"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:academic"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:ebook"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:agents"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:statistics"/>
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</item>
<item rdf:about="http://csde.washington.edu/statnet/">
    <title>Statnet</title>
    <dc:date>2010-09-21T01:42:39+00:00</dc:date>
    <link>http://csde.washington.edu/statnet/</link>
    <dc:creator>howthebodyworks</dc:creator><description><![CDATA[network stats for R
]]></description>
<dc:subject>simss phd academic networks r datamining statistics opensource</dc:subject>
<dc:identifier>https://pinboard.in/u:howthebodyworks/b:19b4686c8df9/</dc:identifier>
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	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:academic"/>
	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:networks"/>
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	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:datamining"/>
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	<rdf:li rdf:resource="https://pinboard.in/u:howthebodyworks/t:opensource"/>
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