Pinboard (cshalizi) https://pinboard.in/u:cshalizi/public/ recent bookmarks from cshalizi Markov and the Birth of Chain Dependence Theory on JSTOR 2026-06-01T13:58:12+00:00 https://www.jstor.org/stable/1403785?seq=1 cshaliziin_NB markov_models history_of_mathematics markov.a.a. ergodic_theory mixing free_will https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b76b51010206/ [2602.04250] A Note on Physical Dependence and Mixing Conditions for Triangular Arrays 2026-02-05T14:10:03+00:00 https://arxiv.org/abs/2602.04250 cshalizi to_read mixing re:codename:catherine_wheel in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:a231e8b97c1d/ [2510.02471] Predictive inference for time series: why is split conformal effective despite temporal dependence? 2025-11-10T14:26:55+00:00 https://arxiv.org/abs/2510.02471 cshalizi to:NB time_series prediction mixing conformal_prediction barber.rina_foygel https://pinboard.in/ https://pinboard.in/u:cshalizi/b:09b188b2229e/ Statistical learning for $$psi $$ -weakly dependent processes | Statistical Inference for Stochastic Processes 2025-09-03T14:22:34+00:00 https://link.springer.com/article/10.1007/s11203-025-09329-6 cshalizi to:NB learning_theory mixing time_series https://pinboard.in/ https://pinboard.in/u:cshalizi/b:47b97e670aaa/ [2203.04395] Equivalences of Geometric Ergodicity of Markov Chains 2024-12-11T16:02:48+00:00 https://arxiv.org/abs/2203.04395 cshalizi to:NB markov_models mixing ergodic_theory re:almost_none https://pinboard.in/ https://pinboard.in/u:cshalizi/b:bb278df058e6/ [2109.02224] On Empirical Risk Minimization with Dependent and Heavy-Tailed Data 2023-12-14T11:31:16+00:00 https://arxiv.org/abs/2109.02224 cshalizi to:NB to_read learning_theory mixing heavy_tails learning_under_dependence https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9123f4f94745/ [2303.08992] Law of large numbers and central limit theorem for ergodic quantum processes 2023-04-22T13:55:53+00:00 https://arxiv.org/abs/2303.08992 cshalizi stochastic_processes quantum_mechanics ergodic_theory mixing central_limit_theorem re:almost_none in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:0ab8f9922f41/ [2203.04163] Localization Schemes: A Framework for Proving Mixing Bounds for Markov Chains 2022-06-09T08:19:32+00:00 https://arxiv.org/abs/2203.04163 cshalizi to:NB stochastic_processes mixing markov_models martingales https://pinboard.in/ https://pinboard.in/u:cshalizi/b:03c6185cd447/ Stochastic Limit Theory: An Introduction for Econometricians - Oxford Scholarship 2022-01-12T02:14:25+00:00 https://oxford.universitypressscholarship.com/view/10.1093/oso/9780192844507.001.0001/oso-9780192844507?rskey=nzm83v&result=113 cshalizi to:NB books:noted stochastic_processes convergence_of_stochastic_processes asymptotics ergodic_theory martingales mixing to_download https://pinboard.in/ https://pinboard.in/u:cshalizi/b:51efb0da9d46/ [2108.00997] Generalization bounds for nonparametric regression with $β-$mixing samples 2021-08-11T18:56:55+00:00 https://arxiv.org/abs/2108.00997 cshalizi in_NB to_read learning_theory ergodic_theory mixing statistics learning_under_dependence https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5d2f8d41532e/ [2106.13947] Optimal prediction of Markov chains with and without spectral gap 2021-06-30T02:57:36+00:00 https://arxiv.org/abs/2106.13947 cshalizi to:NB prediction time_series mixing markov_models statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:be4dfa48c5ee/ [2011.00308] Mixing it up: A general framework for Markovian statistics 2021-06-25T14:55:04+00:00 https://arxiv.org/abs/2011.00308 cshalizi to:NB to_read markov_models minimax empirical_processes statistical_inference_for_stochastic_processes re:almost_none mixing statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:60fea291f30b/ [2106.07054] Inferring the mixing properties of an ergodic process 2021-06-21T16:21:49+00:00 https://arxiv.org/abs/2106.07054 cshaliziγ. An analogous goodness-of-fit test is proposed for the ℓ1 norm of the sequence of β-mixing coefficients of a stationary ergodic process. Moreover, the procedure gives rise to an asymptotically consistent test for independence." --- Well, at least they cite us (even if they say we're too vague to follow!).]]> to:NB to_read mixing dependence_measures lugosi.gabor statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5ad1449205e5/ [2104.12929] Central Limit Theorems for High Dimensional Dependent Data 2021-04-29T03:27:23+00:00 https://arxiv.org/abs/2104.12929 cshalizi to:NB central_limit_theorem mixing stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:1888293e2873/ [2007.10874] Central limit theorems for stationary random fields under weak dependence with application to ambit and mixed moving average fields 2021-04-08T14:25:42+00:00 https://arxiv.org/abs/2007.10874 cshalizi to:NB mixing dependence_measures random_fields central_limit_theorem stochastic_processes to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f6d72975cae5/ On some basic features of strictly stationary, reversible Markov chains - Bradley - - Journal of Time Series Analysis - Wiley Online Library 2021-01-10T19:43:19+00:00 https://onlinelibrary.wiley.com/doi/abs/10.1111/jtsa.12583?campaign=wolacceptedarticle cshalizi to:NB stochastic_processes markov_models mixing https://pinboard.in/ https://pinboard.in/u:cshalizi/b:34be5d457c2b/ [1909.11773] Rapid mixing of a Markov chain for an exponentially weighted aggregation estimator 2019-10-01T17:34:33+00:00 https://arxiv.org/abs/1909.11773 cshalizi to:NB markov_models monte_carlo mixing computational_statistics statistics pollard.david https://pinboard.in/ https://pinboard.in/u:cshalizi/b:6dad1ea4a033/ Merlevède , Peligrad , Utev : Functional CLT for martingale-like nonstationary dependent structures 2019-09-26T00:58:23+00:00 https://projecteuclid.org/euclid.bj/1569398764 cshalizi to:NB central_limit_theorem mixing non-stationarity stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:4365022dd63e/ Testing nonstationary and absolutely regular nonlinear time series models | SpringerLink 2019-08-28T15:10:22+00:00 https://link.springer.com/article/10.1007/s11203-018-9194-8 cshalizi to:NB time_series goodness-of-fit mixing statistics empirical_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:8b738190090b/ [1810.04496] On maxima of stationary fields 2019-08-20T14:52:31+00:00 https://arxiv.org/abs/1810.04496 cshalizivn,MAn≤vn))+o(1), for some increasing sequence of sets An of size o(nd). For a class of fields satisfying a local mixing condition, including m-dependent ones, the theorem holds with a constant finite A replacing An. The above results lead to new formulas for the extremal index for random fields."]]> to:NB extreme_values random_fields stochastic_processes mixing re:almost_none https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b48b11d4a911/ [1908.00845] Iterations of dependent random maps and exogeneity in nonlinear dynamics 2019-08-05T14:13:32+00:00 https://arxiv.org/abs/1908.00845 cshalizi to:NB stochastic_processes ergodic_theory mixing time_series dynamical_systems statistics statistical_inference_for_stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:47d385d293f6/ Functional Gaussian Approximation for Dependent Structures - Florence Merlevede; Magda Peligrad; Sergey Utev - Oxford University Press 2019-05-24T23:55:52+00:00 https://global.oup.com/academic/product/functional-gaussian-approximation-for-dependent-structures-9780198826941?cc=us&lang=en# cshalizi to:NB central_limit_theorem stochastic_processes convergence_of_stochastic_processes mixing ergodic_theory re:almost_none books:noted https://pinboard.in/ https://pinboard.in/u:cshalizi/b:a47e5db7c861/ [1808.08811] Exponential inequalities for nonstationary Markov Chains 2018-09-19T14:24:12+00:00 https://arxiv.org/abs/1808.08811 cshalizi to:NB to_read markov_models mixing learning_theory to_teach:childs_garden_of_statistical_learning_theory https://pinboard.in/ https://pinboard.in/u:cshalizi/b:90d514e3a092/ Asymptotic Theory of Weakly Dependent Random Processes | Emmanuel Rio | Springer 2017-09-13T22:39:50+00:00 http://www.springer.com/gp/book/9783662543221?wt_mc=Alerts.NBA.Sep-13 cshalizi books:noted stochastic_processes mixing ergodic_theory markov_models in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:6799ddedf364/ Learning Theory Estimates with Observations from General Stationary Stochastic Processes | Neural Computation | MIT Press Journals 2016-11-23T18:21:15+00:00 http://www.mitpressjournals.org/doi/abs/10.1162/NECO_a_00870 cshalizi stochastic_processes learning_theory dependence_measures mixing ergodic_theory statistics re:XV_for_mixing re:your_favorite_dsge_sucks in_NB to_teach:childs_garden_of_statistical_learning_theory https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5c929691bae6/ [1308.4117] Comparison Theorems for Gibbs Measures 2016-09-07T14:49:37+00:00 http://arxiv.org/abs/1308.4117 cshalizi statistical_mechanics stochastic_processes ergodic_theory mixing van_handel.ramon in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:11c81a1313cd/ Blockwise bootstrap of the estimated empirical process based on psi -weakly dependent observations - Springer 2016-03-14T18:13:05+00:00 http://link.springer.com/article/10.1007/s11203-015-9120-2?wt_mc=alerts.TOCjournals cshalizi to:NB empirical_processes bootstrap mixing stochastic_processes statistical_inference_for_stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5a3cc34601d4/ [1506.02903] Mixing Time Estimation in Reversible Markov Chains from a Single Sample Path 2015-07-14T09:40:58+00:00 http://arxiv.org/abs/1506.02903 cshalizi to:NB mixing markov_models statistical_inference_for_stochastic_processes monte_carlo kontorovich.aryeh kith_and_kin https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e1dbbfcc18e8/ Information flow on graphs | The Information Structuralist 2015-05-20T16:00:24+00:00 https://infostructuralist.wordpress.com/2014/05/03/information-flow-on-graphs/ cshalizi information_theory cellular_automata stochastic_processes mixing random_fields markov_models to:blog https://pinboard.in/ https://pinboard.in/u:cshalizi/b:270fa18b9ed2/ Dehling , Durieu , Tusche : Approximating class approach for empirical processes of dependent sequences indexed by functions 2015-01-24T14:13:31+00:00 http://projecteuclid.org/euclid.bj/1402488943 cshalizi empirical_processes approximation stochastic_processes markov_models dynamical_systems ergodic_theory mixing in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b57eb1847383/ [1501.03059] A Bernstein-type Inequality for Some Mixing Processes and Dynamical Systems with an Application to Learning 2015-01-19T15:13:56+00:00 http://arxiv.org/abs/1501.03059 cshalizi deviation_inequalities stochastic_processes mixing learning_theory statistics in_NB to_teach:childs_garden_of_statistical_learning_theory https://pinboard.in/ https://pinboard.in/u:cshalizi/b:4ffd5aaf0d45/ Forecasting Nonstationary Time Series: From Theory to Algorithms 2014-12-17T18:09:44+00:00 http://www.cims.nyu.edu/~vitaly/pub/fts.pdf cshalizi to:NB mixing learning_theory re:your_favorite_dsge_sucks re:XV_for_mixing time_series have_read to_teach:childs_garden_of_statistical_learning_theory https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5aee25e7a5fb/ Concentration Inequalities and Estimation of Conditional Probabilities 2014-06-14T14:08:29+00:00 https://www.ma.utexas.edu/mp_arc/c/05/05-65.pdf cshalizi concentration_of_measure stochastic_processes re:AoS_project have_read mixing in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:4ae738278aa9/ [1405.0608] Approximate tensorization of entropy at high temperature 2014-05-09T20:53:01+00:00 http://arxiv.org/abs/1405.0608 cshalizi stochastic_processes to_read entableted concentration_of_measure mixing in_NB via:mraginsky https://pinboard.in/ https://pinboard.in/u:cshalizi/b:52e3b1fab041/ [1404.2802] Mixing and Concentration by Ricci Curvature 2014-04-20T18:33:15+00:00 http://arxiv.org/abs/1404.2802 cshalizi to:NB mixing markov_models stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:61d9b456af96/ [1404.0645] Moment bounds and concentration inequalities for slowly mixing dynamical systems 2014-04-14T19:42:20+00:00 http://arxiv.org/abs/1404.0645 cshalizi mixing concentration_of_measure dynamical_systems central_limit_theorem stochastic_processes in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:6437bba409a5/ [1404.0295] Hitting time statistics for observations of dynamical systems 2014-04-14T19:41:47+00:00 http://arxiv.org/abs/1404.0295 cshalizi to:NB mixing recurrence_times dynamical_systems stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:21b41cb1cb4a/ [0707.0322] Consistency of support vector machines for forecasting the evolution of an unknown ergodic dynamical system from observations with unknown noise 2014-03-12T20:37:56+00:00 http://arxiv.org/abs/0707.0322 cshalizi dynamical_systems mixing ergodic_theory nonparametrics statistics prediction support-vector_machines steinwart.ingo time_series statistical_inference_for_stochastic_processes re:your_favorite_dsge_sucks re:XV_for_mixing to_read in_NB entableted https://pinboard.in/ https://pinboard.in/u:cshalizi/b:a11e92b7fc51/ Berkes , Liu , Wu : Komlós–Major–Tusnády approximation under dependence 2014-03-12T19:14:12+00:00 http://projecteuclid.org/euclid.aop/1393251303 cshalizi to:NB mixing ergodic_theory convergence_of_stochastic_processes central_limit_theorem stochastic_processes re:almost_none https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e3a22f3fd2d2/ An Empirical Process Central Limit Theorem for Multidimensional Dependent Data - Springer 2014-03-10T15:11:23+00:00 http://link.springer.com/article/10.1007/s10959-012-0450-3?wt_mc=alerts.TOCjournals cshalizi empirical_processes stochastic_processes mixing re:almost_none in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:143a1f4e33e0/ [1209.0633] Nonparametric regression on hidden phi-mixing variables: identifiability and consistency of a pseudo-likelihood based estimation procedure 2014-02-20T01:04:28+00:00 http://arxiv.org/abs/1209.0633 cshalizi to:NB statistical_inference_for_stochastic_processes time_series filtering statistics mixing https://pinboard.in/ https://pinboard.in/u:cshalizi/b:4a6c43d17081/ IEEE Xplore - Recursive Nonparametric Estimation for Time Series 2014-01-28T01:20:56+00:00 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6675825 cshalizi to:NB nonparametrics statistical_inference_for_stochastic_processes statistics mixing https://pinboard.in/ https://pinboard.in/u:cshalizi/b:99f7fbd379b7/ [1312.2128] On the rate of convergence in Wasserstein distance of the empirical measure 2013-12-11T15:54:58+00:00 http://arxiv.org/abs/1312.2128 cshalizi0. We provide some satisfying non-asymptotic Lp-bounds and concentration inequalities, for any values of p>0 and d≥1. We extend also the non asymptotic Lp-bounds to stationary ρ-mixing sequences, Markov chains, and to some interacting particle systems."]]> probability stochastic_processes mixing deviation_inequalities markov_models in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:a7c197e4d1ae/ [1309.4859] Predictive PAC Learning and Process Decompositions 2013-09-20T12:59:20+00:00 http://arxiv.org/abs/1309.4859 cshalizi self-centered in_NB mixing ergodic_theory stochastic_processes learning_theory mixture_models prediction kontorovich.aryeh https://pinboard.in/ https://pinboard.in/u:cshalizi/b:761883d720df/ Bayesian Representations of Stochastic Processes Under Learning: de Finetti Revisited (Jackson, Kalai and Smorodinsky, Econometrica 67 (1999): 875--893) 2013-09-09T03:34:37+00:00 http://www.jstor.org/discover/10.2307/2999460?uid=3739864&uid=2129&uid=2&uid=70&uid=4&uid=3739256&sid=21102630678603 cshalizi$\mu =\int_{\Theta}\mu _{\theta }d\lambda (\theta)$. Among these, a natural representation is one whose components $(\mu _{\theta}\text{'}{\rm s})$ are "learnable" (one can approximate μ θ by conditioning μ on observation of the process) and "sufficient for prediction" ($\mu _{\theta}\text{'}{\rm s}$ predictions are not aided by conditioning on observation of the process). We show the existence and uniqueness of such a representation under a suitable asymptotic mixing condition on the process. This representation can be obtained by conditioning on the tail-field of the process, and any learnable representation that is sufficient for prediction is asymptotically like the tail-field representation. This result is related to the celebrated de Finetti theorem, but with exchangeability weakened to an asymptotic mixing condition, and with his conclusion of a decomposition into i.i.d. component distributions weakened to components that are learnable and sufficient for prediction." - A bit astonishing there's no mention of de-Finetti-like theorems for partial exchangeability, or even of the ergodic decomposition.]]> stochastic_processes mixing learning_theory re:almost_none jackson.matthew_o. ergodic_theory re:pac-and-mar not_quite_scooped_exactly have_read in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5645e3ec2909/ now publishers – Long Range Dependence 2013-08-15T15:19:37+00:00 http://www.nowpublishers.com/articles/foundations-and-trends-in-stochastic-systems/STO-004 cshalizi to:NB long-range_dependence stochastic_processes ergodic_theory mixing to_read large_deviations https://pinboard.in/ https://pinboard.in/u:cshalizi/b:dfd6679f032a/ [1109.2694] Kernel density estimation for stationary random fields 2013-07-29T19:57:46+00:00 http://arxiv.org/abs/1109.2694 cshalizi to:NB density_estimation statistics random_fields mixing https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5d228c8d75c8/ [1304.7960] A strictly stationary $beta$-mixing process satisfying the central limit theorem but not the weak invariance principle 2013-05-01T16:31:13+00:00 http://arxiv.org/abs/1304.7960 cshalizi to:NB mixing central_limit_theorem re:almost_none https://pinboard.in/ https://pinboard.in/u:cshalizi/b:4f6bd9420402/ [1304.5113] A note on weak convergence of the sequential multivariate empirical process under strong mixing 2013-04-22T17:23:25+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_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:c7b219da085f/ [1304.2621] Central limit theorems in linear dynamics 2013-04-10T21:29:11+00:00 http://arxiv.org/abs/1304.2621 cshalizi to:NB mixing central_limit_theorem ergodic_theory stochastic_processes dynamical_systems https://pinboard.in/ https://pinboard.in/u:cshalizi/b:ee98841bea95/ [1303.6999] Exponential ergodicity for Markov processes with random switching 2013-03-29T17:10:00+00:00 http://arxiv.org/abs/1303.6999 cshalizi to:NB markov_models stochastic_processes ergodic_theory mixing https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e119a9841a75/ Rev. Mod. Phys. 61, 981 (1989): The dynamic origin of increasing entropy 2013-03-26T19:34:38+00:00 http://dx.doi.org/10.1103/RevModPhys.61.981 cshalizi have_read ergodic_theory mixing arrow_of_time statistical_mechanics non-equilibrium mackey.michael_c. in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:627b52250eb8/ [1303.4537] A Sequential Empirical Central Limit Theorem for Multiple Mixing Processes with Application to B-Geometrically Ergodic Markov Chains 2013-03-20T01:56:30+00:00 http://arxiv.org/abs/1303.4537 cshalizi to:NB stochastic_processes empirical_processes mixing ergodic_theory https://pinboard.in/ https://pinboard.in/u:cshalizi/b:6d870f677691/ Central Limit Theorems for Weakly Dependent Random Fields - Springer 2013-02-12T01:43:44+00:00 http://link.springer.com/chapter/10.1007%2F978-3-642-33305-7_10 cshalizi to:NB central_limit_theorem stochastic_processes mixing random_fields https://pinboard.in/ https://pinboard.in/u:cshalizi/b:d234ea141b38/ Central limit theorem for triangular arrays of non-homogeneous Markov chains - Springer 2012-12-03T00:09:31+00:00 http://link.springer.com/article/10.1007/s00440-011-0371-6 cshalizi to:NB central_limit_theorem mixing markov_models stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:269b080dba60/ Geometric ergodicity and the spectral gap of non-reversible Markov chains 2012-10-12T13:52:16+00:00 http://www.springerlink.com/content/1v2n1v06776kp01u/ cshalizi markov_models stochastic_processes ergodic_theory mixing in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:10a41762541a/ [1208.1720] Mixing Coefficients Between Discrete and Real Random Variables: Computation and Properties 2012-09-04T02:42:20+00:00 http://arxiv.org/abs/1208.1720 cshalizi to:NB to_read mixing statistical_inference_for_stochastic_processes nonparametrics vidyasagar.mathukumalli https://pinboard.in/ https://pinboard.in/u:cshalizi/b:34584e82bf9b/ Tong , van Handel : Ergodicity and stability of the conditional distributions of nondegenerate Markov chains 2012-08-10T17:53:03+00:00 http://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.aoap/1344614202 cshalizi to_read ergodic_theory mixing filtering markov_models stochastic_processes re:almost_none van_handel.ramon in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:884d46bd9925/ [1204.0608] Mixing times in evolutionary game dynamics 2012-04-14T17:47:48+00:00 http://arxiv.org/abs/1204.0608 cshalizi to:NB evolutionary_game_theory markov_models mixing re:do-institutions-evolve stochastic_processes metastability https://pinboard.in/ https://pinboard.in/u:cshalizi/b:43be49123f9d/ Relative Entropy and Exponential Deviation Bounds for General Markov Chains 2012-04-11T18:21:22+00:00 https://netfiles.uiuc.edu/meyn/www/spm_files/Papers_pdf/markovISIT05.pdf cshalizi markov_models stochastic_processes meyn.sean kontoyiannis.ioannis mixing information_theory have_read in_NB deviation_inequalities via:mraginsky https://pinboard.in/ https://pinboard.in/u:cshalizi/b:d1e83ba94bee/ Ferré , Hervé , Ledoux : Limit theorems for stationary Markov processes with L2-spectral gap 2012-04-11T13:54:23+00:00 http://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.aihp/1334148205 cshalizi 0 for (c) and (d)). For the statements (b) and (d), a Markov nonlattice condition is also assumed as in the independent case. All the results are derived under the assumption that the Markov process has an invariant probability distribution π, is stationary and has the -spectral gap property (that is, (Xt)t∈ℕ is ρ-mixing in the discrete-time case). The case where is non-stationary is briefly discussed. As an application, we derive a Berry–Esseen bound for the M-estimators associated with ρ-mixing Markov chains."]]> stochastic_processes markov_models ergodic_theory mixing statistical_inference_for_stochastic_processes in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:c621855f5656/ [1203.5245] Qualitative robustness of statistical functionals under strong mixing 2012-03-26T00:44:51+00:00 http://arxiv.org/abs/1203.5245 cshalizi statistics mixing statistical_inference_for_stochastic_processes learning_theory in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:65a50e88573d/ Doukhan, Massart, Rio: Invariance principles for absolutely regular empirical processes 2012-02-24T05:15:01+00:00 http://www.numdam.org/item?id=AIHPB_1995__31_2_393_0 cshaliziempirical_processes stochastic_processes mixing central_limit_theorem to_read re:your_favorite_dsge_sucks in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:227ed863c23e/ [1202.4283] Fast rates in learning with dependent observations 2012-02-21T03:42:32+00:00 http://arxiv.org/abs/1202.4283 cshalizi learning_theory mixing ergodic_theory re:your_favorite_dsge_sucks re:XV_for_mixing have_read in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:d4316c2a0b5b/ [1201.4579] Limit theorems for stationary Markov processes with L2-spectral gap 2012-01-28T16:51:17+00:00 http://arxiv.org/abs/1201.4579 cshalizi 0$ for (c) and (d)). For the statements (b) and (d), a Markov nonlattice condition is also assumed as in the independent case. All the results are derived under the assumption that the Markov process $(X_t)_{tin T}$ has an invariant probability distribution $pi$, is stationary and has the $L^2(pi)$-spectral gap property (that is, $(X_t)tin N}$ is $rho$-mixing in the discrete-time case). The case where $(X_t)_{tin T}$ is non-stationary is briefly discussed. As an application, we derive a Berry-Esseen bound for the M-estimators associated with $rho$-mixing Markov chains."]]> markov_models stochastic_processes central_limit_theorem mixing ergodic_theory in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b63611506168/ A Lemma and a Conjecture on the Cost of Rearrangements 2012-01-05T02:28:48+00:00 http://archive.numdam.org/article/RSMUP_2003__110__97_0.pdf cshalizimathematics mixing via:slaniel in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:c7df1bf2fa64/ A Bernstein type inequality and moderate deviations for weakly dependent sequences 2011-11-07T18:56:14+00:00 http://www.springerlink.com/content/c38664053l348582/ cshalizi to_read re:XV_for_mixing re:your_favorite_dsge_sucks concentration_of_measure mixing ergodic_theory stochastic_processes moderate_deviations in_NB deviation_inequalities https://pinboard.in/ https://pinboard.in/u:cshalizi/b:23f7c782d807/ [math/0305026] Chains with complete connections: General theory, uniqueness, loss of memory and mixing properties 2011-10-28T21:26:55+00:00 http://arxiv.org/abs/math/0305026 cshalizi in_NB chains_with_complete_connections re:AoS_project markov_models stochastic_processes re:almost_none mixing ergodic_theory have_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:8532b3f414ae/ [1110.2529] The Generalization Ability of Online Algorithms for Dependent Data 2011-10-13T12:33:26+00:00 http://arxiv.org/abs/1110.2529 cshalizi learning_theory individual_sequence_prediction ergodic_theory mixing re:growing_ensemble_project re:XV_for_mixing stability_of_learning concentration_of_measure have_read re:your_favorite_dsge_sucks in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:0891bd9c9846/ [1107.1794] Some Aspects of Modeling Dependence in Copula-based Markov chains 2011-07-12T15:53:12+00:00 http://arxiv.org/abs/1107.1794 cshalizi markov_models copulas ergodic_theory mixing statistics in_NB https://pinboard.in/u:cshalizi/b:c748acf8a876/