Pinboard (cshalizi)
https://pinboard.in/u:cshalizi/public/
recent bookmarks from cshaliziA short note on the median-of-means estimator (Yen-Chi Chen, 2020)2026-04-23T16:43:42+00:00
https://faculty.washington.edu/yenchic/short_note/note_MoM.pdf
cshalizito:NB have_read statistics heavy_tails estimation empirical_processeshttps://pinboard.in/https://pinboard.in/u:cshalizi/b:ee5135168ce3/[2503.21576] Empirical Measures and Strong Laws of Large Numbers in Categorical Probability2025-03-31T13:50:16+00:00
https://arxiv.org/abs/2503.21576
cshalizito:NB probability empirical_processes abstract_nonsensehttps://pinboard.in/https://pinboard.in/u:cshalizi/b:9cec99f9353f/[2501.13813] Regularizing random points by deleting a few2025-02-03T00:30:24+00:00
https://arxiv.org/abs/2501.13813
cshalizito:NB probability empirical_processes monte_carlo via:?https://pinboard.in/https://pinboard.in/u:cshalizi/b:97e6f84d0342/[2403.16651] A short proof of the Dvoretzky--Kiefer--Wolfowitz--Massart inequality2024-12-11T15:52:43+00:00
https://arxiv.org/abs/2403.16651
cshalizito:NB empirical_processes to_read re:almost_none to_teach:childs_garden_of_statistical_learning_theoryhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:847d245f036a/Geometric Discrepancy: An Illustrated Guide | SpringerLink2024-07-17T18:50:19+00:00
https://link.springer.com/book/10.1007/978-3-642-03942-3
cshalizibooks:noted mathematics geometry empirical_processes via:vaguery in_NB downloadedhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:1be9139b4e2a/[2309.17016] Efficient Agnostic Learning with Average Smoothness2023-12-08T17:15:57+00:00
https://arxiv.org/abs/2309.17016
cshaliziin_NB nonparametrics learning_theory empirical_processes kith_and_kin kontorovich.aryeh hanneke.stevehttps://pinboard.in/https://pinboard.in/u:cshalizi/b:372bb023a730/A plug-in uniform law of large numbers - Biased and Inefficient2023-06-15T19:18:32+00:00
https://notstatschat.rbind.io/2022/09/28/uniform-law-of-large-numbers/
cshalizihave_read ergodic_theory empirical_processes lumley.thomas learning_theory re:HEAS in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:1dfcf0d1d3f9/[2305.02960] Majorizing Measures, Codes, and Information2023-05-06T22:44:46+00:00
https://arxiv.org/abs/2305.02960
cshalizito_read empirical_processes information_theory raginsky.maxim in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:1d743b81e124/[2202.04415] Towards Empirical Process Theory for Vector-Valued Functions: Metric Entropy of Smooth Function Classes2022-06-13T17:00:24+00:00
https://arxiv.org/abs/2202.04415
cshalizito:NB learning_theory empirical_processes hilbert_space via:?https://pinboard.in/https://pinboard.in/u:cshalizi/b:fe711e83cc23/[2011.00308] Mixing it up: A general framework for Markovian statistics2021-06-25T14:55:04+00:00
https://arxiv.org/abs/2011.00308
cshalizito:NB to_read markov_models minimax empirical_processes statistical_inference_for_stochastic_processes re:almost_none mixing statisticshttps://pinboard.in/https://pinboard.in/u:cshalizi/b:60fea291f30b/Empirical process results for exchangeable arrays2021-04-14T15:55:48+00:00
https://projecteuclid.org/journals/annals-of-statistics/volume-49/issue-2/Empirical-process-results-for-exchangeable-arrays/10.1214/20-AOS1981.short
cshalizito:NB graphons exchangeability empirical_processes bootstrap re:network_bootstraps to_readhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:704083f7b44d/[2101.06936] Wasserstein Convergence Rate for Empirical Measures of Markov Chains2021-01-19T18:33:59+00:00
https://arxiv.org/abs/2101.06936
cshalizito:NB markov_models empirical_processes concentration_of_measure stochastic_processeshttps://pinboard.in/https://pinboard.in/u:cshalizi/b:f9a9a23f65e4/[2012.15678] On Gaussian Approximation for M-Estimator2021-01-03T20:05:42+00:00
https://arxiv.org/abs/2012.15678
cshalizito:NB central_limit_theorem estimation statistics empirical_processes re:HEAShttps://pinboard.in/https://pinboard.in/u:cshalizi/b:580f8c5bf237/[2012.10320] Local Dvoretzky-Kiefer-Wolfowitz confidence bands2020-12-21T04:40:03+00:00
https://arxiv.org/abs/2012.10320
cshalizi \epsilon\Big)$ for different values of $\uu,\ou\in[0,1]$. Such local controls naturally appear for instance when studying estimation error of spectral risk-measures (such as the conditional value at risk), where $[\uu,\ou]$ is typically [0,α] or [1−α,1] for a risk level α, after reshaping the CDF F of the considered distribution into U by the general inverse transform F−1. Extending a proof technique from Smirnov, we provide exact expressions of the local quantities $\Pr\Big(\sup_{u\in [\uu,\ou]} U_n(u)-U(u) > \epsilon\Big)$ and $\Pr\Big(\sup_{u\in [\uu,\ou]} U(u)-U_n(u) > \epsilon\Big)$ for each $n,\epsilon,\uu,\ou$. Interestingly these quantities, seen as a function of ϵ, can be easily inverted numerically into functions of the probability level δ. Although not explicit, they can be computed and tabulated. We plot such expressions and compare them to the classical bound ln(1/δ)2n‾‾‾‾‾√ provided by Massart inequality. Last, we extend the local concentration results holding individually for each n to time-uniform concentration inequalities holding simultaneously for all n, revisiting a reflection inequality by James, which is of independent interest for the study of sequential decision making strategies."]]>to:NB empirical_processeshttps://pinboard.in/https://pinboard.in/u:cshalizi/b:c7d8f7494fc8/[2003.13530] Bounding the expectation of the supremum of empirical processes indexed by Hölder classes2020-12-18T10:31:59+00:00
https://arxiv.org/abs/2003.13530
cshalizito:NB empirical_processes learning_theoryhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:38793d7ed1b5/Lei : Convergence and concentration of empirical measures under Wasserstein distance in unbounded functional spaces2019-12-03T19:47:19+00:00
https://projecteuclid.org/euclid.bj/1574758845
cshaliziconcentration_of_measure empirical_processes statistics in_NB kith_and_kin lei.jinghttps://pinboard.in/https://pinboard.in/u:cshalizi/b:7156f6d26814/[1910.09319] Empirical Process of Multivariate Gaussian under General Dependence2019-10-29T14:25:00+00:00
https://arxiv.org/abs/1910.09319
cshalizigaussian_processes stochastic_processes empirical_processes re:almost_none in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:ac75e1d721b1/[1910.07485] Excess risk bounds in robust empirical risk minimization2019-10-17T14:07:49+00:00
https://arxiv.org/abs/1910.07485
cshalizito:NB learning_theory empirical_processes probability statistics heavy_tails to_teach:childs_garden_of_statistical_learning_theoryhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:bbde8fa32918/Dolera , Regazzini : Uniform rates of the Glivenko–Cantelli convergence and their use in approximating Bayesian inferences2019-09-13T13:02:42+00:00
https://projecteuclid.org/euclid.bj/1568362049
cshaliziempirical_processes statistics re:fitness_sampling in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:f773f86d023c/[1702.08109] Variational Analysis of Constrained M-Estimators2019-09-12T16:24:45+00:00
https://arxiv.org/abs/1702.08109
cshalizito:NB estimation empirical_processes statistics nonparametricshttps://pinboard.in/https://pinboard.in/u:cshalizi/b:e5d16319e505/[1809.06522] Concentration Inequalities for the Empirical Distribution2019-09-12T00:15:30+00:00
https://arxiv.org/abs/1809.06522
cshaliziconcentration_of_measure deviation_inequalities empirical_processes statistics probability to_read in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:c03a05b6c59d/[1909.02088] On Least Squares Estimation under Heteroscedastic and Heavy-Tailed Errors2019-09-09T03:46:50+00:00
https://arxiv.org/abs/1909.02088
cshalizito:NB regression empirical_processes statistics heavy_tails nonparametricshttps://pinboard.in/https://pinboard.in/u:cshalizi/b:fffcfe887104/Testing nonstationary and absolutely regular nonlinear time series models | SpringerLink2019-08-28T15:10:22+00:00
https://link.springer.com/article/10.1007/s11203-018-9194-8
cshalizito:NB time_series goodness-of-fit mixing statistics empirical_processeshttps://pinboard.in/https://pinboard.in/u:cshalizi/b:8b738190090b/Tan , Zhang : Doubly penalized estimation in additive regression with high-dimensional data2019-08-03T19:29:04+00:00
https://projecteuclid.org/euclid.aos/1564797857
cshalizito:NB statistics regression additive_models nonparametrics empirical_processeshttps://pinboard.in/https://pinboard.in/u:cshalizi/b:a91a49a02b12/[1907.09244] Fast rates for empirical risk minimization with cadlag losses with bounded sectional variation norm2019-07-24T14:02:23+00:00
https://arxiv.org/abs/1907.09244
cshalizito:NB learning_theory method_of_sieves regression empirical_processes statistics van_der_laan.markhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:50e7cd068af5/Han , Wellner : Convergence rates of least squares regression estimators with heavy-tailed errors2019-05-26T22:14:28+00:00
https://projecteuclid.org/euclid.aos/1558425646
cshalizito:NB regression empirical_processes statistics heavy_tails nonparametricshttps://pinboard.in/https://pinboard.in/u:cshalizi/b:a745d4cc291e/Lee , Song : Stable limit theorems for empirical processes under conditional neighborhood dependence2019-05-25T03:01:30+00:00
https://projecteuclid.org/euclid.bj/1551862848
cshalizito_read empirical_processes random_fields stochastic_processes central_limit_theorem in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:f93b70f7625b/Block Bootstrap for the Empirical Process of Long-Range Dependent Data - Tewes - 2017 - Journal of Time Series Analysis - Wiley Online Library2017-10-12T23:22:20+00:00
http://onlinelibrary.wiley.com/doi/10.1111/jtsa.12256/abstract
cshalizistochastic_processes time_series statistics bootstrap empirical_processes long-range_dependence in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:ac0214bb2adb/Optimal Rate of Convergence for Empirical Quantiles and Distribution Functions for Time Series - Jirak - 2016 - Journal of Time Series Analysis - Wiley Online Library2016-10-18T20:58:30+00:00
http://onlinelibrary.wiley.com/doi/10.1111/jtsa.12189/abstract
cshalizito:NB empirical_processes nonparametrics statistics time_series central_limit_theoremhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:5f76a7a363f4/[1508.05906] Chaining, Interpolation, and Convexity2016-09-07T14:53:37+00:00
http://arxiv.org/abs/1508.05906
cshaliziempirical_processes learning_theory approximation convexity functional_analysis van_handel.ramon in_NB to_teach:childs_garden_of_statistical_learning_theoryhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:724678402496/[1510.04740] Semiparametric theory and empirical processes in causal inference2016-09-01T19:20:22+00:00
http://arxiv.org/abs/1510.04740
cshalizito:NB statistics causal_inference nonparametrics empirical_processes to_read kith_and_kin kennedy.edward_h.https://pinboard.in/https://pinboard.in/u:cshalizi/b:bb7c068be950/[1607.06534] The Landscape of Empirical Risk for Non-convex Losses2016-07-25T03:15:03+00:00
http://arxiv.org/abs/1607.06534
cshalizilearning_theory empirical_processes optimization in_NB high-dimensional_statistics to_teach:childs_garden_of_statistical_learning_theory via:mraginskyhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:bbd8d05b53e2/Estimation and Testing Under Sparsity | Sara van de Geer | Springer2016-07-06T13:53:56+00:00
http://www.springer.com/us/book/9783319327730
cshalizito:NB books:noted statistics sparsity high-dimensional_statistics lasso hypothesis_testing confidence_sets van_de_geer.sara to_read empirical_processeshttps://pinboard.in/https://pinboard.in/u:cshalizi/b:a21d87b7abc5/Blockwise bootstrap of the estimated empirical process based on psi -weakly dependent observations - Springer2016-03-14T18:13:05+00:00
http://link.springer.com/article/10.1007/s11203-015-9120-2?wt_mc=alerts.TOCjournals
cshalizito:NB empirical_processes bootstrap mixing stochastic_processes statistical_inference_for_stochastic_processeshttps://pinboard.in/https://pinboard.in/u:cshalizi/b:5a3cc34601d4/Arcones , Gine : Limit Theorems for $U$-Processes2015-12-09T00:27:53+00:00
https://projecteuclid.org/euclid.aop/1176989128
cshaliziu-statistics empirical_processes deviation_inequalities vc-dimension central_limit_theorem re:smoothing_adjacency_matrices in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:fbf2713f12b2/Measures of Complexity - Festschrift for Alexey Chervonenkis | Vladimir Vovk | Springer2015-10-26T03:51:34+00:00
http://www.springer.com/us/book/9783319218519
cshalizito:NB learning_theory empirical_processes vc-dimension books:noted to_teach:childs_garden_of_statistical_learning_theoryhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:7a0909ffb330/From Uniform Laws of Large Numbers to Uniform Ergodic Theorems2015-08-27T00:24:46+00:00
http://www.maths.manchester.ac.uk/~goran/lectures.pdf
cshaliziin_NB ergodic_theory vc-dimension learning_theory stochastic_processes empirical_processes have_read books:recommended to_teach:childs_garden_of_statistical_learning_theoryhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:f5f9b778314c/Chernozhukov , Chetverikov , Kato : Gaussian approximation of suprema of empirical processes2015-02-23T07:23:52+00:00
http://projecteuclid.org/euclid.aos/1407420009
cshaliziempirical_processes to_read in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:4c682f5d4a08/Dehling , Durieu , Tusche : Approximating class approach for empirical processes of dependent sequences indexed by functions2015-01-24T14:13:31+00:00
http://projecteuclid.org/euclid.bj/1402488943
cshaliziempirical_processes approximation stochastic_processes markov_models dynamical_systems ergodic_theory mixing in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:b57eb1847383/Lederer , van de Geer : New concentration inequalities for suprema of empirical processes2015-01-24T14:12:37+00:00
http://projecteuclid.org/euclid.bj/1411134452
cshaliziempirical_processes concentration_of_measure deviation_inequalities van_de_geer.sara stochastic_processes to_read in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:0877957415cc/Trashorras , Wintenberger : Large deviations for bootstrapped empirical measures2015-01-24T14:10:22+00:00
http://projecteuclid.org/euclid.bj/1411134447
cshalizibootstrap empirical_processes large_deviations stochastic_processes statistics re:almost_none in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:d04a91aae66c/[1409.2090] On the asymptotics of random forests2015-01-20T14:07:18+00:00
http://arxiv.org/abs/1409.2090
cshalizito:NB decision_trees ensemble_methods empirical_processes statistics random_forestshttps://pinboard.in/https://pinboard.in/u:cshalizi/b:1fb865de58fb/[1409.8557] Statistical Theory for High-Dimensional Models2015-01-20T02:01:08+00:00
http://arxiv.org/abs/1409.8557
cshalizistatistics high-dimensional_statistics concentration_of_measure empirical_processes regression lasso van_de_geer.sara in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:4290f1c88bdc/[math/0410072] Higher criticism for detecting sparse heterogeneous mixtures2014-10-18T01:04:15+00:00
http://arxiv.org/abs/math/0410072
cshalizito:NB multiple_testing hypothesis_testing empirical_processes statistics donoho.david jin.jiashun tukey.john_w. have_read re:network_differences to:bloghttps://pinboard.in/https://pinboard.in/u:cshalizi/b:1877e29a7c8c/Koul , Stute : Nonparametric model checks for time series2014-08-07T16:09:12+00:00
http://projecteuclid.org/euclid.aos/1018031108
cshalizistatistics goodness-of-fit time_series empirical_processes in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:603b42bac578/Probability in High Dimension2014-07-09T13:26:22+00:00
https://www.princeton.edu/~rvan/ORF570.pdf
cshaliziconcentration_of_measure empirical_processes probability high-dimensional_probability learning_theory vc-dimension van_handel.ramon via:arsyed re:almost_none in_NB to_teach:childs_garden_of_statistical_learning_theoryhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:f6d6eb8bb7ee/[1401.3034] Inference for Monotone Trends Under Dependence2014-03-10T18:02:18+00:00
http://arxiv.org/abs/1401.3034
cshalizito:NB nonparametrics regression statistics empirical_processeshttps://pinboard.in/https://pinboard.in/u:cshalizi/b:356ff9f12790/An Empirical Process Central Limit Theorem for Multidimensional Dependent Data - Springer2014-03-10T15:11:23+00:00
http://link.springer.com/article/10.1007/s10959-012-0450-3?wt_mc=alerts.TOCjournals
cshaliziempirical_processes stochastic_processes mixing re:almost_none in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:143a1f4e33e0/[1402.2718] Concentration of random polytopes around the expected convex hull2014-02-18T00:38:09+00:00
http://arxiv.org/abs/1402.2718
cshaliziempirical_processes probability high-dimensional_probability in_NB geometryhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:c473014dfaa8/[1402.2918] Confidence Bands for Distribution Functions: A New Look at the Law of the Iterated Logarithm2014-02-13T18:22:03+00:00
http://arxiv.org/abs/1402.2918
cshaliziempirical_processes statistics confidence_sets re:pli-R in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:bdea1795ab46/[1312.1005] Squared-Norm Empirical Process in Banach Space2014-01-02T17:54:55+00:00
http://arxiv.org/abs/1312.1005
cshaliziempirical_processes kith_and_kin vu.vince lei.jing in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:75dfd1030d20/[1312.5894] Weak Convergence of the Sequential Empirical Process of some Long-Range Dependent Sequences with Respect to a Weighted Norm2013-12-26T17:16:17+00:00
http://arxiv.org/abs/1312.5894
cshaliziempirical_processes stochastic_processes long-range_dependence in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:caac9d6b56f0/Preuß , Vetter , Dette : A test for stationarity based on empirical processes2013-12-03T15:55:03+00:00
http://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.bj/1386078618
cshalizito:NB empirical_processes stochastic_processes statistical_inference_for_stochastic_processes hypothesis_testing statistics non-stationarityhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:2d8ed594c1dd/[1310.5796] Relative Deviation Learning Bounds and Generalization with Unbounded Loss Functions2013-10-23T14:15:38+00:00
http://arxiv.org/abs/1310.5796
cshalizilearning_theory vc-dimension empirical_processes have_read in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:4e3b59d92bd3/[1310.5523] On the uniform convergence of empirical norms and inner products, with application to causal inference2013-10-23T14:11:54+00:00
http://arxiv.org/abs/1310.5523
cshaliziconcentration_of_measure empirical_processes causal_inference statistics nonparametrics van_de_geer.sara to_read entableted in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:6c426a1eb91c/The Bernstein–Orlicz norm and deviation inequalities - Springer2013-09-19T15:29:01+00:00
http://link.springer.com/article/10.1007/s00440-012-0455-y
cshaliziempirical_processes deviation_inequalities van_de_geer.sara in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:de384e3fe4bc/Testing for a Change of the Innovation Distribution in Nonparametric Autoregression: The Sequential Empirical Process Approach - Selk - 2013 - Scandinavian Journal of Statistics - Wiley Online Library2013-09-17T22:28:10+00:00
http://onlinelibrary.wiley.com/doi/10.1111/sjos.12030/abstract
cshalizito:NB time_series change-point_problem nonparametrics regression statistics empirical_processes hypothesis_testinghttps://pinboard.in/https://pinboard.in/u:cshalizi/b:72096b56b6e7/Dedecker , Merlevède , Rio : Strong approximation results for the empirical process of stationary sequences2013-09-12T20:03:08+00:00
http://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.aop/1378991852
cshalizito:NB empirical_processes stochastic_processes dynamical_systemshttps://pinboard.in/https://pinboard.in/u:cshalizi/b:420cc1ef8399/[1212.6906] Central Limit Theorems and Multiplier Bootstrap when p is much larger than n2013-09-09T03:36:11+00:00
http://arxiv.org/abs/1212.6906
cshalizito:NB empirical_processes stochastic_processes approximation central_limit_theorem bootstrap statistics probabilityhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:038f7e73d1e5/Uniform-in-Bandwidth Functional Limit Laws - Springer2013-08-17T19:00:06+00:00
http://link.springer.com/article/10.1007/s10959-011-0376-1
cshaliziempirical_processes density_estimation statistics convergence_of_stochastic_processes in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:95b3eab71ec7/[1307.1565] Concentration inequalities for smooth random fields2013-07-08T16:32:27+00:00
http://arxiv.org/abs/1307.1565
cshalizirandom_fields empirical_processes concentration_of_measure stochastic_processes re:almost_none in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:145934415469/[1305.6408] When uniform weak convergence fails: empirical processes for dependence functions via epi- and hypographs2013-05-29T13:44:24+00:00
http://arxiv.org/abs/1305.6408
cshaliziconvergence_of_stochastic_processes empirical_processes probability statistics copulas in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:d90fd135f357/[1305.5618] A general approach to the joint asymptotic analysis of statistics from sub-samples2013-05-27T12:15:21+00:00
http://arxiv.org/abs/1305.5618
cshalizito_read re:XV_for_mixing empirical_processes bootstrap time_series convergence_of_stochastic_processes statistical_inference_for_stochastic_processes statistics in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:dac13484b7b7/[1304.5113] A note on weak convergence of the sequential multivariate empirical process under strong mixing2013-04-22T17:23:25+00:00
http://arxiv.org/abs/1304.5113
cshalizi1$, which slightly improves upon existing results in the literature that are based on mixing rates depending on the dimension $d$."]]>to:NB mixing ergodic_theory empirical_processes stochastic_processeshttps://pinboard.in/https://pinboard.in/u:cshalizi/b:c7b219da085f/[math/0512554] On weakly bounded empirical processes2013-04-13T22:13:37+00:00
http://arxiv.org/abs/math/0512554
cshalizi1$. We also present some geometric applications of this approach, based on properties of the random operator $\Gamma=k^{-1/2}\sum_{i=1}^k \inr{X_i,\cdot}e_i$, where the $(X_i)_{i=1}^k$ are sampled according to an isotropic, log-concave measure on $\R^n$."]]>empirical_processes in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:64eeea38042e/[1303.4537] A Sequential Empirical Central Limit Theorem for Multiple Mixing Processes with Application to B-Geometrically Ergodic Markov Chains2013-03-20T01:56:30+00:00
http://arxiv.org/abs/1303.4537
cshalizito:NB stochastic_processes empirical_processes mixing ergodic_theoryhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:6d870f677691/Kuelbs , Kurtz , Zinn : A CLT for empirical processes involving time-dependent data2013-03-10T01:14:54+00:00
http://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.aop/1362750942
cshalizito:NB empirical_processes stochastic_processes central_limit_theorem kurtz.thomas_g.https://pinboard.in/https://pinboard.in/u:cshalizi/b:9da8e56eddc3/[1212.6885] Gaussian approximation of suprema of empirical processes2013-01-07T23:08:30+00:00
http://arxiv.org/abs/1212.6885
cshalizistochastic_processes empirical_processes learning_theory re:almost_none in_NBhttps://pinboard.in/https://pinboard.in/u:cshalizi/b:2efec7591cb9/Testing Monotonicity of Regression Functions – An Empirical Process Approach - BIRKE - 2012 - Scandinavian Journal of Statistics - Wiley Online Library2012-12-18T14:02:04+00:00
http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9469.2012.00820.x/abstract
cshalizito:NB to_read regression statistics model_checking to_teach:undergrad-ADA empirical_processeshttps://pinboard.in/https://pinboard.in/u:cshalizi/b:b28a508a7443/Bonnéry , Breidt , Coquet : Uniform convergence of the empirical cumulative distribution function under informative selection from a finite population2012-11-13T21:56:57+00:00
http://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.bj/1352727815
cshalizito:NB learning_theory statistics empirical_processes survey_samplinghttps://pinboard.in/https://pinboard.in/u:cshalizi/b:35e97456a76a/