Pinboard (cshalizi) https://pinboard.in/u:cshalizi/public/ recent bookmarks from cshalizi [2406.04089] On Limitation of Transformer for Learning HMMs 2025-09-17T13:23:42+00:00 https://arxiv.org/abs/2406.04089 cshalizi to:NB have_skimmed neural_networks time_series automata_theory state-space_models large_language_models_(so_called) via:? https://pinboard.in/ https://pinboard.in/u:cshalizi/b:a9f4e9105545/ [2308.09543] Latent State Models of Training Dynamics 2025-03-10T13:48:28+00:00 https://arxiv.org/abs/2308.09543 cshalizi to:NB neural_networks optimization state-space_models https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9ff283321c2c/ [2502.02472] SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations 2025-02-17T19:24:40+00:00 https://arxiv.org/abs/2502.02472 cshalizi to:NB stochastic_differential_equations state-space_models simulation-based_inference to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:7c8643cc83a2/ Universal Approximation of Input-Output Maps by Temporal Convolutional Nets 2024-12-11T15:53:54+00:00 https://proceedings.neurips.cc/paper/2019/hash/39555391eb0624a439c5131b1bb8a2e0-Abstract.html cshalizi to:NB neural_networks state-space_models raginsky.maxim https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e0f980082d66/ Bagged Filters for Partially Observed Interacting Systems: Journal of the American Statistical Association: Vol 0, No 0 2022-06-11T04:57:01+00:00 https://www.tandfonline.com/doi/full/10.1080/01621459.2021.1974867 cshalizi to:NB time_series state_estimation state-space_models particle_filters ensemble_methods ionides.edward https://pinboard.in/ https://pinboard.in/u:cshalizi/b:737c28aede3c/ [2107.11253] State, global and local parameter estimation using local ensemble Kalman filters: applications to online machine learning of chaotic dynamics 2021-07-26T14:56:43+00:00 https://arxiv.org/abs/2107.11253 cshalizi state-space_models state_estimation misspecification time_series to_read statistics in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b8af6c2cb494/ Maximum likelihood estimation of hidden Markov models for continuous longitudinal data with missing responses and dropout 2021-07-01T13:30:50+00:00 https://arxiv.org/abs/2106.15948 cshalizi to:NB time_series state-space_models missing_data statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:ed7cf93460a6/ [2002.05211] Bagged filters for partially observed interacting systems 2021-06-28T03:45:08+00:00 https://arxiv.org/abs/2002.05211 cshalizi to:NB state-space_models ensemble_methods particle_filters spatio-temporal_statistics statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:0b4c5b2a7b88/ [2101.01157] Partially observed Markov processes with spatial structure via the R package spatPomp 2021-06-28T03:44:01+00:00 https://arxiv.org/abs/2101.01157 cshalizi to:NB state-space_models spatio-temporal_statistics statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:3157a05da40b/ [2106.12936] Fundamental limits for learning hidden Markov model parameters 2021-06-25T15:09:23+00:00 https://arxiv.org/abs/2106.12936 cshalizi to:NB state-space_models minimax statistical_inference_for_stochastic_processes statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:8c037ff7a877/ [2106.09327] Minimax Estimation of Partially-Observed Vector AutoRegressions 2021-06-24T20:38:58+00:00 https://arxiv.org/abs/2106.09327 cshalizi to:NB time_series state-space_models statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:ed155f37eb03/ [2106.01645] Rényi Divergence in General Hidden Markov Models 2021-06-07T03:55:45+00:00 https://arxiv.org/abs/2106.01645 cshalizi to:NB stochastic_processes markov_models state-space_models information_theory https://pinboard.in/ https://pinboard.in/u:cshalizi/b:acea15a6abd1/ [2105.14394] Asymptotic Normality of the Posterior Distributions in a Class of Hidden Markov Models 2021-06-01T13:33:50+00:00 https://arxiv.org/abs/2105.14394 cshalizi to:NB bayesian_consistency state-space_models statistical_inference_for_stochastic_processes statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:63324b05df3f/ [2105.11490] Hidden Markov and semi-Markov models: When and why are these models useful to classify states in time series data? 2021-05-26T18:30:10+00:00 https://arxiv.org/abs/2105.11490 cshalizi to:NB state-space_models time_series classifiers state_estimation misspecification to_teach:data_over_space_and_time statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:14bc8be5c08a/ [2105.04912] On Unbiased Score Estimation for Partially Observed Diffusions 2021-05-12T18:31:32+00:00 https://arxiv.org/abs/2105.04912 cshalizi to:NB statistical_inference_for_stochastic_processes state-space_models stochastic_differential_equations filtering https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b23596cf3c5c/ [2103.08055] Modeling Longitudinal Dynamics of Comorbidities 2021-04-08T14:27:41+00:00 https://arxiv.org/abs/2103.08055 cshalizi to:NB time_series statistics state-space_models https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f197db6a97a3/ [2101.03801] Hidden Markov chains and fields with observations in Riemannian manifolds 2021-01-12T22:39:27+00:00 https://arxiv.org/abs/2101.03801 cshalizi to:NB markov_models state-space_models random_fields statistics_on_manifolds https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b0b4911debdd/ [2008.11477] Bellman filtering for state-space models 2021-01-12T22:36:48+00:00 https://arxiv.org/abs/2008.11477 cshalizi state_estimation filtering optimization state-space_models in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:eb0e619a36af/ Du Roy de Chaumaray , Marbac , Navarro : Mixture of hidden Markov models for accelerometer data 2020-12-19T16:39:06+00:00 https://projecteuclid.org/euclid.aoas/1608346901 cshalizi to:NB mixture_models state-space_models to_teach:data_over_space_and_time https://pinboard.in/ https://pinboard.in/u:cshalizi/b:3613e129d8f3/ [2012.05294] A modified Susceptible-Infected-Recovered model for observed under-reported incidence data 2020-12-12T18:14:57+00:00 https://arxiv.org/abs/2012.05294 cshalizi to:NB epidemic_models state-space_models coronavirus_pandemic_of_2019-- to_teach:data_over_space_and_time https://pinboard.in/ https://pinboard.in/u:cshalizi/b:8a8258127354/ [2002.02001] A guide to state-space modeling of ecological time series 2020-11-23T17:42:40+00:00 https://arxiv.org/abs/2002.02001 cshalizi to:NB state-space_models markov_models ecology statistics to_teach:data_over_space_and_time https://pinboard.in/ https://pinboard.in/u:cshalizi/b:176ad5a8bc65/ Model Checking for Hidden Markov Models: Journal of Computational and Graphical Statistics: Vol 0, No 0 2020-11-20T04:15:52+00:00 https://www.tandfonline.com/doi/full/10.1080/10618600.2020.1743295 cshalizi to:NB state-space_models model_checking goodness-of-fit to_teach:data_over_space_and_time https://pinboard.in/ https://pinboard.in/u:cshalizi/b:0da48f41614a/ Analyticity of Entropy Rates of Continuous-State Hidden Markov Models - IEEE Journals & Magazine 2020-11-16T16:02:36+00:00 https://ieeexplore.ieee.org/document/8804216 cshalizi to:NB entropy information_theory markov_models state-space_models doucet.arnaud https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9e84242609c9/ Robust estimation for discrete‐time state space models - Aeberhard - - Scandinavian Journal of Statistics - Wiley Online Library 2020-11-15T20:53:35+00:00 https://doi.org/10.1111/sjos.12482 cshalizi to:NB state-space_models time_series statistics state_estimation https://pinboard.in/ https://pinboard.in/u:cshalizi/b:206d62949f9e/ Stochastic dynamics filtering and optimization | Control systems and optimization | Cambridge University Press 2020-01-09T17:57:40+00:00 https://www.cambridge.org/us/academic/subjects/engineering/control-systems-and-optimization/stochastic-dynamics-filtering-and-optimization?format=HB cshalizi books:noted optimization filtering state_estimation stochastic_processes state-space_models re:almost_none books:suggest_to_library in_NB downloaded https://pinboard.in/ https://pinboard.in/u:cshalizi/b:30fbcfbf0054/ Unsupervised identification of the internal states that shape natural behavior | Nature Neuroscience 2019-11-26T15:27:40+00:00 https://www.nature.com/articles/s41593-019-0533-x cshalizi to:NB neuroscience state-space_models time_series psychology inference_to_latent_objects statistics to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:8bb625685c95/ [1910.04221] Likelihood-based Inference for Partially Observed Epidemics on Dynamic Networks 2019-10-11T16:36:27+00:00 https://arxiv.org/abs/1910.04221 cshalizi epidemics_on_networks state-space_models statistical_inference_for_stochastic_processes statistics in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e4dc67bf4832/ [1909.12890] A Dual Characterization of Observability for Stochastic Systems 2019-10-01T16:22:10+00:00 https://arxiv.org/abs/1909.12890 cshalizi to:NB control_theory_and_control_engineering state_estimation state-space_models markov_models stochastic_differential_equations https://pinboard.in/ https://pinboard.in/u:cshalizi/b:bcedaf81dac4/ [1909.10287] Mean Field approach to stochastic control with partial information 2019-09-26T18:03:50+00:00 https://arxiv.org/abs/1909.10287 cshalizi to:NB control_theory_and_control_engineering stochastic_processes filtering state_estimation state-space_models https://pinboard.in/ https://pinboard.in/u:cshalizi/b:88d010408e74/ [1909.01506] Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control 2019-09-10T13:00:40+00:00 https://arxiv.org/abs/1909.01506 cshalizi to:NB control_theory_and_control_engineering differential_geometry stochastic_processes state-space_models https://pinboard.in/ https://pinboard.in/u:cshalizi/b:0bb51a0eb553/ [1906.11395] A Tutorial on Concentration Bounds for System Identification 2019-09-04T19:47:41+00:00 https://arxiv.org/abs/1906.11395 cshalizi concentration_of_measure large_deviations time_series statistics state-space_models in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:c658d73ae1ea/ [1908.07204] Forecasting observables with particle filters: Any filter will do! 2019-08-21T13:15:34+00:00 https://arxiv.org/abs/1908.07204 cshalizi time_series particle_filters prediction state_estimation state-space_models to_teach:data_over_space_and_time statistics in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:6295f6655b43/ [1906.09410] A reaction network scheme which implements inference and learning for Hidden Markov Models 2019-08-20T15:27:24+00:00 https://arxiv.org/abs/1906.09410 cshalizi to:NB em_algorithm markov_models state-space_models biochemical_networks wiuf.carsten pointless_but_nonetheless_awesome biological_computers https://pinboard.in/ https://pinboard.in/u:cshalizi/b:df0502950c8a/ [1302.5484] Input-output equivalence and identifiability: some simple generalizations of the differential algebra approach 2019-08-20T14:06:02+00:00 https://arxiv.org/abs/1302.5484 cshalizi to:NB state-space_models identifiability algebra statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:57f9c49a2194/ Parallelising Particle Filters with Butterfly Interactions - Heine - - Scandinavian Journal of Statistics - Wiley Online Library 2019-08-19T02:44:44+00:00 https://onlinelibrary.wiley.com/doi/abs/10.1111/sjos.12408?af=R cshalizi to:NB computational_statistics particle_filters time_series state-space_models state_estimation re:fitness_sampling https://pinboard.in/ https://pinboard.in/u:cshalizi/b:cef9fdc64128/ [1805.12217] Introducing shrinkage in heavy-tailed state space models to predict equity excess returns 2019-07-30T17:47:56+00:00 https://arxiv.org/abs/1805.12217 cshalizi to:NB state-space_models heavy_tails time_series statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f06afcc09c84/ Introduction to Hidden Semi-Markov Models by John van der Hoek 2019-06-15T17:28:29+00:00 https://www.cambridge.org/core/books/introduction-to-hidden-semimarkov-models/081D73832BA173BE7133B1DA4E2ED0E8#fndtn-information cshalizi to:NB books:noted markov_models state-space_models statistics time_series genomics books:owned https://pinboard.in/ https://pinboard.in/u:cshalizi/b:28c3136e1e63/ [1811.11834] Asymptotic Analysis of Model Selection Criteria for General Hidden Markov Models 2019-06-06T13:50:27+00:00 https://arxiv.org/abs/1811.11834 cshalizi to:NB model_selection information_criteria state-space_models markov_models statistical_inference_for_stochastic_processes statistics singh.sumeetpal https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5adf62069468/ [1905.10857] Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models 2019-05-28T17:08:30+00:00 https://arxiv.org/abs/1905.10857 cshalizi causal_inference causal_discovery state-space_models time_series non-stationarity statistics kith_and_kin glymour.clark to_read zhang.kun in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:fa5a8c6e24c2/ Lehéricy : Consistent order estimation for nonparametric hidden Markov models 2019-05-25T03:00:08+00:00 https://projecteuclid.org/euclid.bj/1544605253 cshalizi to:NB model_selection markov_models state-space_models statistics statistical_inference_for_stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:de655588d7d3/ Kantas , Doucet , Singh , Maciejowski , Chopin : On Particle Methods for Parameter Estimation in State-Space Models 2019-05-25T02:34:25+00:00 https://projecteuclid.org/euclid.ss/1439220716 cshalizi to:NB particle_filters statistical_inference_for_stochastic_processes state-space_models statistics time_series to_teach:data_over_space_and_time have_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:eb99758930ca/ A Composite Likelihood Framework for Analyzing Singular DSGE Models | The Review of Economics and Statistics | MIT Press Journals 2019-01-04T03:27:21+00:00 https://www.mitpressjournals.org/doi/abs/10.1162/rest_a_00718 cshalizi state-space_models economics time_series macroeconomics statistics likelihood re:your_favorite_dsge_sucks in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:3f15d77b79b3/ Neural Decoding: A Predictive Viewpoint | Neural Computation | MIT Press Journals 2017-12-01T15:18:06+00:00 http://www.mitpressjournals.org/doi/abs/10.1162/neco_a_01020 cshalizi to:NB have_read neural_coding_and_decoding statistics model_selection state-space_models kith_and_kin ventura.valerie todorova.sonia https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b5937b9933a6/ A Robbins–Monro Algorithm for Non-Parametric Estimation of NAR Process with Markov Switching: Consistency - Fermin - 2017 - Journal of Time Series Analysis - Wiley Online Library 2017-04-27T17:27:07+00:00 http://onlinelibrary.wiley.com/doi/10.1111/jtsa.12237/abstract cshalizi time_series stochastic_approximation statistics online_learning markov_models state-space_models in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:0b80a5c10fa1/ Links Between Multiplicity Automata, Observable Operator Models and Predictive State Representations -- a Unified Learning Framework 2016-11-30T02:09:54+00:00 http://www.jmlr.org/papers/v16/thon15a.html cshalizi to:NB re:AoS_project stochastic_processes statistics prediction state-space_models automata_theory https://pinboard.in/ https://pinboard.in/u:cshalizi/b:25727a8ab045/ [1204.2477] A Simple Explanation of A Spectral Algorithm for Learning Hidden Markov Models 2016-11-30T01:58:35+00:00 https://arxiv.org/abs/1204.2477 cshalizi to:NB spectral_methods re:AoS_project markov_models state-space_models statistics time_series estimation https://pinboard.in/ https://pinboard.in/u:cshalizi/b:384a791646c5/ [1606.08650] Approximate Smoothing and Parameter Estimation in High-Dimensional State-Space Models 2016-09-07T14:54:27+00:00 http://arxiv.org/abs/1606.08650 cshalizi to:NB particle_filters time_series statistical_inference_for_stochastic_processes filtering stochastic_processes state-space_models high-dimensional_statistics singh.sumeetpal_s. statistics re:fitness_sampling https://pinboard.in/ https://pinboard.in/u:cshalizi/b:a76b4d887144/ [1607.06494] Stochastic Control via Entropy Compression 2016-07-25T03:32:07+00:00 http://arxiv.org/abs/1607.06494 cshalizi to:NB state-space_models information_theory control_theory_and_control_engineering via:mraginsky https://pinboard.in/ https://pinboard.in/u:cshalizi/b:8115355da86c/ Delay Embeddings for Forced Systems. II. Stochastic Forcing | SpringerLink 2016-07-20T22:33:14+00:00 http://link.springer.com/article/10.1007%2Fs00332-003-0534-4 cshalizi to:NB to_read time_series state-space_reconstruction state-space_models statistics dynamical_systems have_skimmed https://pinboard.in/ https://pinboard.in/u:cshalizi/b:1a4e1d863703/ SFIHMM (Estimating Hidden Markov Models) 2016-06-05T03:43:50+00:00 http://tuvalu.santafe.edu/~simon/styled-8/ cshalizi to:NB markov_models state-space_models kith_and_kin dedeo.simon https://pinboard.in/ https://pinboard.in/u:cshalizi/b:ff59c392310d/ Inference in finite state space non parametric Hidden Markov Models and applications - Springer 2016-01-09T17:34:13+00:00 http://link.springer.com/article/10.1007/s11222-014-9523-8 cshalizi to:NB markov_models state-space_models statistics nonparametrics time_series https://pinboard.in/ https://pinboard.in/u:cshalizi/b:33814323d310/ [1507.06346] Evaluation of Spectral Learning for the Identification of Hidden Markov Models 2015-08-05T15:00:28+00:00 http://arxiv.org/abs/1507.06346 cshalizi to:NB spectral_methods markov_models state-space_models statistics time_series computational_statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f6ad5cde987e/ Crisan , Míguez : Particle-kernel estimation of the filter density in state-space models 2015-01-24T14:11:26+00:00 http://projecteuclid.org/euclid.bj/1411134448 cshalizi particle_filters density_estimation filtering state_estimation state-space_models statistics computational_statistics in_NB kernel_smoothing https://pinboard.in/ https://pinboard.in/u:cshalizi/b:77a953685926/ [1411.5634] Earthquake Forecasting Using Hidden Markov Models 2015-01-22T00:25:08+00:00 http://arxiv.org/abs/1411.5634 cshalizi to:NB earthquakes geology time_series prediction state-space_models markov_models statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5dc056c604b1/ [1412.8695] On Particle Methods for Parameter Estimation in State-Space Models 2015-01-20T02:09:33+00:00 http://arxiv.org/abs/1412.8695 cshalizi to:NB particle_filters time_series statistics estimation state-space_models https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5154ac2a01ea/ Vidyasagar, M.: Hidden Markov Processes: Theory and Applications to Biology 2014-10-02T20:16:09+00:00 http://press.princeton.edu/titles/10286.html cshalizi books:noted markov_models state-space_models em_algorithm large_deviations stochastic_processes statistical_inference_for_stochastic_processes statistics genomics bioinformatics books:owned in_NB vidyasagar.mathukumalli https://pinboard.in/ https://pinboard.in/u:cshalizi/b:47a239958696/ Spectral learning of weighted automata - Springer 2014-07-31T14:51:43+00:00 http://link.springer.com/article/10.1007/s10994-013-5416-x?wt_mc=alerts.TOCjournals cshalizi to:NB to_read re:AoS_project spectral_methods automata_theory grammar_induction markov_models state-space_models learning_theory machine_learning statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:d678b734bce5/ Adaptively learning probabilistic deterministic automata from data streams - Springer 2014-07-31T14:50:44+00:00 http://link.springer.com/article/10.1007/s10994-013-5408-x?wt_mc=alerts.TOCjournals cshalizi to:NB to_read re:AoS_project grammar_induction markov_models state-space_models automata_theory machine_learning statistics learning_theory https://pinboard.in/ https://pinboard.in/u:cshalizi/b:8f5ba4f6e75b/ PAutomaC: a probabilistic automata and hidden Markov models learning competition - Springer 2014-07-31T14:49:51+00:00 http://link.springer.com/article/10.1007/s10994-013-5409-9?wt_mc=alerts.TOCjournals cshalizi to:NB to_read re:AoS_project grammar_induction markov_models state-space_models machine_learning https://pinboard.in/ https://pinboard.in/u:cshalizi/b:42c98a8f6199/ Rydén : EM versus Markov chain Monte Carlo for estimation of hidden Markov models: a computational perspective 2014-07-31T13:21:49+00:00 http://projecteuclid.org/euclid.ba/1340370402 cshalizi to:NB em_algorithm monte_carlo markov_models state-space_models estimation statistics computational_statistics ryden.tobias https://pinboard.in/ https://pinboard.in/u:cshalizi/b:a2dacf87ada3/ [1404.4210] Nonparametric identification of hidden Markov models 2014-04-20T18:20:53+00:00 http://arxiv.org/abs/1404.4210 cshalizi to:NB state-space_models markov_models statistics time_series https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9cd721f63c91/ [1403.6804] A simple modification for improving inference of non-linear dynamical systems 2014-04-03T18:37:17+00:00 http://arxiv.org/abs/1403.6804 cshalizi particle_filters state-space_models state_estimation statistical_inference_for_stochastic_processes statistics re:fitness_sampling in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:2aa48c6a16dd/ Parameter Estimation for Hidden Markov Models with Intractable Likelihoods - Dean - 2014 - Scandinavian Journal of Statistics - Wiley Online Library 2014-03-13T14:28:58+00:00 http://onlinelibrary.wiley.com/doi/10.1111/sjos.12077/abstract;jsessionid=81B7064F9C37EF342CB590A9F76A40E8.f01t02?systemMessage=Wiley+Online+Library+will+be+disrupted+Saturday%2C+15+March+from+10%3A00-12%3A00+GMT+%2806%3A00-08%3A00+EDT%29+for+essential+maintenance cshalizi to:NB estimation state-space_models approximate_bayesian_computation likelihood statistics time_series singh.sumeetpal https://pinboard.in/ https://pinboard.in/u:cshalizi/b:358ed771e574/ Clustering Hidden Markov Models with Variational HEM 2014-03-13T14:18:32+00:00 http://jmlr.org/papers/v15/coviello14a.html cshalizi to:NB markov_models state-space_models clustering time_series variational_inference statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:dc91071effcf/ Chan , Lai : A general theory of particle filters in hidden Markov models and some applications 2014-02-20T22:21:27+00:00 http://projecteuclid.org/euclid.aos/1387313393 cshalizi particle_filters filtering state_estimation martingales statistical_inference_for_stochastic_processes statistics state-space_models markov_models stochastic_processes in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:76bc97fcf610/ Data cloning: easy maximum likelihood estimation for complex ecological models using Bayesian Markov chain Monte Carlo methods - Lele - 2007 - Ecology Letters - Wiley Online Library 2013-12-23T16:48:55+00:00 http://onlinelibrary.wiley.com/doi/10.1111/j.1461-0248.2007.01047.x/abstract?deniedAccessCustomisedMessage=&userIsAuthenticated=false cshalizi monte_carlo likelihood re:stacs have_read statistics estimation state-space_models hierarchical_statistical_models in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:90fcb8b7cf88/ Dubarry , Le Corff : Non-asymptotic deviation inequalities for smoothed additive functionals in nonlinear state-space models 2013-12-03T15:56:43+00:00 http://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.bj/1386078601 cshalizi filtering state_estimation state-space_models markov_models stochastic_processes deviation_inequalities statistical_inference_for_stochastic_processes statistics in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:2c1ce9d96796/ [1310.5951] A Tractable State-Space Model for the Riemannian Manifold of Symmetric Positive Definite Matrices 2013-10-23T19:53:05+00:00 http://arxiv.org/abs/1310.5951 cshalizi to:NB state-space_models statistics_on_manifolds filtering statistics carvalho.carlos_m. https://pinboard.in/ https://pinboard.in/u:cshalizi/b:99985bc07968/ [1305.5797] Convergence in distribution for filtering processes associated to Hidden Markov Models with densities 2013-05-27T03:44:16+00:00 http://arxiv.org/abs/1305.5797 cshalizi to:NB filtering markov_models stochastic_processes state-space_models https://pinboard.in/ https://pinboard.in/u:cshalizi/b:dbfa83e8db55/ [1305.1980] Modeling Temporal Activity Patterns in Dynamic Social Networks 2013-05-10T19:47:08+00:00 http://arxiv.org/abs/1305.1980 cshalizi to:NB social_media time_series markov_models state-space_models connected_time_series kith_and_kin heard_the_talk galstyan.aram ver_steeg.greg https://pinboard.in/ https://pinboard.in/u:cshalizi/b:c2962383be83/