Pinboard (cshalizi) https://pinboard.in/u:cshalizi/public/ recent bookmarks from cshalizi [2402.14419] On nonparametric estimation of the interaction function in particle system models 2024-02-27T20:05:01+00:00 https://arxiv.org/abs/2402.14419 cshalizi to:NB interacting_particle_systems statistical_inference_for_stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:a64b112d1b62/ Stochastic Models of Compartmental Systems on JSTOR 2023-09-29T16:12:22+00:00 https://www.jstor.org/stable/2529945?origin=crossref cshalizi in_NB compartment_models time_series statistical_inference_for_stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f6118c9e68cc/ Phys. Rev. E 62, 1912 (2000) - Symbolic approach for measuring temporal ``irreversibility'' 2023-04-24T21:59:54+00:00 https://journals.aps.org/pre/abstract/10.1103/PhysRevE.62.1912 cshalizi time_series statistical_inference_for_stochastic_processes symbolic_dynamics model_checking hypothesis_testing cleaning_out_the_filing_cabinet_for_the_first_time_since_2005 have_read to:NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:405b67266133/ Phys. Rev. E 51, 3871 (1995) - Symbol sequence statistics in noisy chaotic signal reconstruction 2023-04-24T21:48:32+00:00 https://journals.aps.org/pre/abstract/10.1103/PhysRevE.51.3871 cshalizi symbolic_dynamics dynamical_systems time_series statistical_inference_for_stochastic_processes cleaning_out_the_filing_cabinet_for_the_first_time_since_2005 have_read re:dissertation estimation in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:04d216b60071/ The structure of responses to a sequence of binary events - ScienceDirect 2023-04-24T21:43:30+00:00 https://doi.org/10.1016/0022-2496(66)90020-4 cshalizi have_read markov_models cognitive_science variable-length_markov_models_aka_context_trees statistical_inference_for_stochastic_processes re:AoS_project cleaning_out_the_filing_cabinet_for_the_first_time_since_2005 re:dissertation prediction in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:851a2a33fb27/ Parameter-Based Asymptotics on JSTOR 2023-04-24T21:32:07+00:00 https://www.jstor.org/stable/2336834 cshalizi to_reread estimation statistics cleaning_out_the_filing_cabinet_for_the_first_time_since_2005 likelihood statistical_inference_for_stochastic_processes re:HEAS in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5c278c6fcc6d/ [2109.03582] Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes 2023-02-15T19:57:50+00:00 https://arxiv.org/abs/2109.03582 cshalizi to:NB stochastic_processes kernel_methods causal_discovery time_series statistical_inference_for_stochastic_processes hilbert_space re:codename:catherine_wheel two-sample_tests statistics have_read path_signatures https://pinboard.in/ https://pinboard.in/u:cshalizi/b:105636bb7bad/ Inference Tools for Markov Random Fields on Lattices: The R Package mrf2d | Journal of Statistical Software 2022-06-15T07:49:49+00:00 https://www.jstatsoft.org/article/view/v101i08 cshalizi to:NB random_fields monte_carlo R statistical_inference_for_stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:1a0c75188ebb/ Quasi-likelihood analysis and its applications | SpringerLink 2022-05-11T17:21:09+00:00 https://link.springer.com/article/10.1007/s11203-021-09266-0 cshalizi to:NB likelihood statistical_inference_for_stochastic_processes large_deviations https://pinboard.in/ https://pinboard.in/u:cshalizi/b:658283b0ff7e/ Random-Feature Matching 2021-11-18T03:53:22+00:00 http://bactra.org/weblog/raffle.html cshalizisimulation-based_inference random_features self-promotion statistical_inference_for_stochastic_processes re:codename:catherine_wheel https://pinboard.in/ https://pinboard.in/u:cshalizi/b:393a9631b8b8/ [2107.04592] Statistical Estimation and Nonlinear Filtering in Environmental Pollution 2021-07-12T15:33:37+00:00 https://arxiv.org/abs/2107.04592 cshalizi to:NB state_estimation statistical_inference_for_stochastic_processes statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:fbdbd601df1f/ [2101.09045] Inference of Markov models from trajectories via Large Deviations at Level 2.5 with applications to random walks in disordered media 2021-07-01T13:29:55+00:00 https://arxiv.org/abs/2101.09045 cshalizi to:NB markov_models large_deviations statistical_inference_for_stochastic_processes statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f99b5b88b07a/ [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/ [2106.12064] Assessing epidemic curves for evidence of superspreading 2021-06-25T15:08:38+00:00 https://arxiv.org/abs/2106.12064 cshalizi to:NB epidemiology branching_processes statistical_inference_for_stochastic_processes statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:3ffae71efc21/ [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/ General-order observation-driven models: ergodicity and consistency of the maximum likelihood estimator 2021-06-10T02:15:01+00:00 https://arxiv.org/abs/2106.05201 cshalizi to:NB douc.randal statistical_inference_for_stochastic_processes chains_with_complete_connections time_series statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:ef98218f412d/ [2106.02735] Data-driven discovery of interacting particle systems using Gaussian processes 2021-06-08T13:53:49+00:00 https://arxiv.org/abs/2106.02735 cshalizi interacting_particle_systems statistical_inference_for_stochastic_processes equations_of_motion_from_a_time_series in_NB statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e173d059d86c/ [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/ [2007.08054] Non-parametric estimation of Stochastic Differential Equations from stationary time-series 2021-05-26T15:56:07+00:00 https://arxiv.org/abs/2007.08054 cshalizi to:NB statistical_inference_for_stochastic_processes stochastic_differential_equations equations_of_motion_from_a_time_series statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:90e586c138c0/ [2002.07261] Estimating processes in adapted Wasserstein distance 2021-05-18T13:58:47+00:00 https://arxiv.org/abs/2002.07261 cshalizi to:NB to_read probability stochastic_processes statistical_inference_for_stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:a03061cffd40/ [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/ [2105.04390] Statistical inference for continuous-time locally stationary processes using stationary approximations 2021-05-12T18:16:26+00:00 https://arxiv.org/abs/2105.04390 cshalizi to:NB estimation time_series statistics non-stationarity statistical_inference_for_stochastic_processes re:codename:catherine_wheel https://pinboard.in/ https://pinboard.in/u:cshalizi/b:df61a132f071/ Phys. Rev. E 103, 042310 (2021) - Learning physically consistent differential equation models from data using group sparsity 2021-04-14T14:43:26+00:00 https://journals.aps.org/pre/abstract/10.1103/PhysRevE.103.042310 cshalizi statistical_inference_for_stochastic_processes equations_of_motion_from_a_time_series sparsity in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e7bbb81e3bd3/ Inference of dynamic systems from noisy and sparse data via manifold-constrained Gaussian processes | PNAS 2021-04-14T14:28:26+00:00 https://www.pnas.org/content/118/15/e2020397118 cshalizi to:NB statistical_inference_for_stochastic_processes equations_of_motion_from_a_time_series to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:27ddf268fab0/ Learning interaction kernels in heterogeneous systems of agents from multiple trajectories 2021-04-10T04:24:07+00:00 https://jmlr.org/papers/v22/19-861.html cshalizi to:NB agent-based_models interacting_particle_systems statistical_inference_for_stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:6cd664197918/ [2103.05299] Maximum Likelihood Estimation for Hawkes Processes with self-excitation or inhibition 2021-04-05T21:14:38+00:00 https://arxiv.org/abs/2103.05299 cshalizi to:NB point_processes statistical_inference_for_stochastic_processes statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:2a57f65f092c/ [2003.13555] Causal Inference with Spatio-temporal Data: Estimating the Effects of Airstrikes on Insurgent Violence in Iraq 2021-03-18T04:51:54+00:00 https://arxiv.org/abs/2003.13555 cshalizi to:NB causal_inference spatio-temporal_statistics point_processes statistical_inference_for_stochastic_processes us-iraq_war statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:7b98beae7381/ [2101.04771] Full-Information Estimation of Heterogeneous Agent Models Using Macro and Micro Data 2021-01-14T16:19:25+00:00 https://arxiv.org/abs/2101.04771 cshalizi agent-based_models statistical_inference_for_stochastic_processes likelihood re:codename:catherine_wheel in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f4bad736b775/ [2101.03562] Bootstrapping Non-Stationary Stochastic Volatility 2021-01-12T22:40:45+00:00 https://arxiv.org/abs/2101.03562 cshalizi to:NB bootstrap non-stationarity time_series statistical_inference_for_stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f290a00d25d5/ Indirect Inference for Time Series Using the Empirical Characteristic Function and Control Variates - Davis - - Journal of Time Series Analysis - Wiley Online Library 2021-01-10T19:41:39+00:00 https://onlinelibrary.wiley.com/doi/abs/10.1111/jtsa.12582?campaign=wolacceptedarticle cshalizi to:NB indirect_inference time_series statistical_inference_for_stochastic_processes re:codename:catherine_wheel https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b9d051ae1696/ [2012.14944] Learning non-stationary Langevin dynamics from stochastic observations of latent trajectories 2021-01-03T19:51:23+00:00 https://arxiv.org/abs/2012.14944 cshalizi to:NB stochastic_differential_equations statistical_inference_for_stochastic_processes non-stationarity equations_of_motion_from_a_time_series https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5295ffa6cbe9/ Simulation and Analysis Methods for Stochastic Compartmental Epidemic Models | Annual Review of Statistics and Its Application 2020-12-18T18:46:24+00:00 https://www.annualreviews.org/doi/abs/10.1146/annurev-statistics-061120-034438 cshalizi to:NB epidemic_models statistical_inference_for_stochastic_processes statistics to_teach:data_over_space_and_time https://pinboard.in/ https://pinboard.in/u:cshalizi/b:d89aa3acdce6/ [2012.09141] Change Detection: A functional analysis perspective 2020-12-17T15:28:45+00:00 https://arxiv.org/abs/2012.09141 cshalizi to:NB change-point_problem anomaly_detection principal_components stochastic_processes statistical_inference_for_stochastic_processes statistics spatio-temporal_statistics spatial_statistics time_series hilbert_space https://pinboard.in/ https://pinboard.in/u:cshalizi/b:20d5ce90dc91/ [2012.06391] Learning physically consistent mathematical models from data using group sparsity 2020-12-15T01:36:26+00:00 https://arxiv.org/abs/2012.06391 cshalizi to:NB dynamical_systems statistical_inference_for_stochastic_processes sparsity statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:7760c0b795d9/ [1901.08641] Gibbs posterior convergence and the thermodynamic formalism 2020-12-12T20:03:25+00:00 https://arxiv.org/abs/1901.08641 cshalizi to:NB bayesian_consistency statistical_inference_for_stochastic_processes dynamical_systems large_deviations ergodic_theory nobel.andrew https://pinboard.in/ https://pinboard.in/u:cshalizi/b:2ed738a0f046/ [2012.05601] Bayes posterior convergence for loss functions via almost additive Thermodynamic Formalism 2020-12-12T20:01:26+00:00 https://arxiv.org/abs/2012.05601 cshalizi to:NB bayesian_consistency dynamical_systems statistical_inference_for_stochastic_processes large_deviations https://pinboard.in/ https://pinboard.in/u:cshalizi/b:ca38875160c1/ [2004.09370] Learning Ising models from one or multiple samples 2020-12-12T19:59:01+00:00 https://arxiv.org/abs/2004.09370 cshalizi to:NB ising_model random_fields statistical_inference_for_stochastic_processes statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e567bce5885c/ Sanders , Proutière , Yun : Clustering in Block Markov Chains 2020-12-11T17:26:24+00:00 https://projecteuclid.org/euclid.aos/1607677244 cshalizi to:NB markov_models statistical_inference_for_stochastic_processes clustering statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:7c12332b27bd/ Quasi‐Maximum Likelihood and The Kernel Block Bootstrap for Nonlinear Dynamic Models - Parente - - Journal of Time Series Analysis - Wiley Online Library 2020-11-30T06:16:20+00:00 https://onlinelibrary.wiley.com/doi/abs/10.1111/jtsa.12573 cshalizi to:NB bootstrap time_series statistical_inference_for_stochastic_processes likelihood statistics kernel_smoothing https://pinboard.in/ https://pinboard.in/u:cshalizi/b:fd258f2ba0b0/ [1907.00113] Learning Markov models via low-rank optimization 2020-11-30T03:59:56+00:00 https://arxiv.org/abs/1907.00113 cshalizi to:NB low-rank_approximation markov_models statistics optimization statistical_inference_for_stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:7c5dd99517e8/ Wolfer , Kontorovich : Statistical estimation of ergodic Markov chain kernel over discrete state space 2020-11-20T04:03:29+00:00 https://projecteuclid.org/euclid.bj/1605841254 cshalizi to:NB markov_models statistical_inference_for_stochastic_processes kith_and_kin kontorovich.aryeh https://pinboard.in/ https://pinboard.in/u:cshalizi/b:3b6d2a8bf1e0/ Nickl , Ray : Nonparametric statistical inference for drift vector fields of multi-dimensional diffusions 2020-11-18T21:47:49+00:00 https://projecteuclid.org/euclid.aos/1594972822 cshalizi to:NB stochastic_differential_equations nonparametrics statistical_inference_for_stochastic_processes statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:c8f20a18002d/ Schwartz‐type model selection for ergodic stochastic differential equation models - Eguchi - - Scandinavian Journal of Statistics - Wiley Online Library 2020-11-15T20:52:34+00:00 https://doi.org/10.1111/sjos.12474 cshalizi to:NB stochastic_differential_equations statistical_inference_for_stochastic_processes information_criteria model_selection https://pinboard.in/ https://pinboard.in/u:cshalizi/b:906cb1d004b3/ Phys. Rev. X 10, 021009 (2020) - Learning Force Fields from Stochastic Trajectories 2020-07-13T18:05:16+00:00 https://journals.aps.org/prx/abstract/10.1103/PhysRevX.10.021009 cshalizi to:NB stochastic_differential_equations statistical_inference_for_stochastic_processes learning_theory time_series statistics to_read via:mraginsky https://pinboard.in/ https://pinboard.in/u:cshalizi/b:ed03f7fb2e45/ [2005.03750] Inference, Prediction, and Entropy-Rate Estimation of Continuous-time, Discrete-event Processes 2020-05-29T13:38:49+00:00 https://arxiv.org/abs/2005.03750 cshalizi to:NB to_read prediction markov_models statistical_inference_for_stochastic_processes crutchfield.james_p. entropy_estimation https://pinboard.in/ https://pinboard.in/u:cshalizi/b:01310a468c03/ Model selection tests for nonlinear dynamic models | The Econometrics Journal | Oxford Academic 2020-05-16T18:00:25+00:00 https://doi.org/10.1111/1368-423X.t01-1-00071 cshalizi have_read to_reread model_selection hypothesis_testing statistics misspecification time_series statistical_inference_for_stochastic_processes vuong.quang to_teach:data_over_space_and_time re:HEAS in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:513c1caa4d37/ [0912.4480] Consistency of the maximum likelihood estimator for general hidden Markov models 2020-05-12T23:48:06+00:00 https://arxiv.org/abs/0912.4480 cshalizi to:NB have_read markov_models statistical_inference_for_stochastic_processes statistics_on_manifolds time_series https://pinboard.in/ https://pinboard.in/u:cshalizi/b:45a70689d38a/ [1910.01004] Parameter estimation for SPDEs based on discrete observations in time and space 2020-01-12T23:02:20+00:00 https://arxiv.org/abs/1910.01004 cshalizi to:NB statistical_inference_for_stochastic_processes stochastic_differential_equations spatio-temporal_statistics statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:d13b02320e01/ [1807.05748] Learning Stochastic Differential Equations With Gaussian Processes Without Gradient Matching 2019-11-10T21:46:11+00:00 https://arxiv.org/abs/1807.05748 cshalizi to:NB stochastic_differential_equations statistical_inference_for_stochastic_processes gaussian_processes statistics nonparametrics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5db7dca15d4e/ [1809.05014] Statistical Estimation of Ergodic Markov Chain Kernel over Discrete State Space 2019-10-30T13:36:45+00:00 https://arxiv.org/abs/1809.05014 cshalizi to:NB markov_models statistical_inference_for_stochastic_processes statistics time_series kith_and_kin kontorovich.aryeh to_teach:data_over_space_and_time https://pinboard.in/ https://pinboard.in/u:cshalizi/b:6bd3e4577c01/ [1910.04832] Learning interaction kernels in heterogeneous systems of agents from multiple trajectories 2019-10-24T14:08:30+00:00 https://arxiv.org/abs/1910.04832 cshalizi to:NB interacting_particle_systems statistical_inference_for_stochastic_processes statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:ab103e2c9b23/ [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/ [1908.05517] Epidemic models on social networks -- with inference 2019-08-16T16:40:59+00:00 https://arxiv.org/abs/1908.05517 cshalizi epidemics_on_networks statistical_inference_for_stochastic_processes in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:1f661e2e8f7f/ [1712.01572] Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces 2019-08-15T20:46:18+00:00 https://arxiv.org/abs/1712.01572 cshalizi dynamical_systems statistical_inference_for_stochastic_processes in_NB kernel_methods hilbert_space koopman_operators https://pinboard.in/ https://pinboard.in/u:cshalizi/b:281f6ae34aef/ [1904.05172] Modeling a Hidden Dynamical System Using Energy Minimization and Kernel Density Estimates 2019-08-08T14:20:36+00:00 https://arxiv.org/abs/1904.05172 cshalizi to:NB dynamical_systems time_series inference_to_latent_objects statistics statistical_inference_for_stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:cc3ca7d4c683/ [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/ [1907.10679] Complete maximum likelihood estimation for SEIR epidemic models: theoretical development 2019-07-30T17:54:14+00:00 https://arxiv.org/abs/1907.10679 cshalizi to:NB epidemic_models time_series statistical_inference_for_stochastic_processes statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:2d4ba83904b0/ [1906.08720] Boosting for Dynamical Systems 2019-06-21T19:28:58+00:00 https://arxiv.org/abs/1906.08720 cshalizi to:NB ensemble_methods learning_theory dynamical_systems control_theory_and_control_engineering statistics time_series statistical_inference_for_stochastic_processes hazan.elad https://pinboard.in/ https://pinboard.in/u:cshalizi/b:7e6510daea86/ Importance sampling for partially observed temporal epidemic models | SpringerLink 2019-06-19T20:45:07+00:00 https://link.springer.com/article/10.1007/s11222-018-9827-1 cshalizi to:NB particle_filters epidemic_models stochastic_processes statistical_inference_for_stochastic_processes statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:ad479c1c442d/ Inference for ergodic diffusions plus noise - Nakakita - 2019 - Scandinavian Journal of Statistics - Wiley Online Library 2019-06-15T16:55:12+00:00 https://onlinelibrary.wiley.com/doi/abs/10.1111/sjos.12360?af=R cshalizi to:NB stochastic_processes statistical_inference_for_stochastic_processes statistics time_series https://pinboard.in/ https://pinboard.in/u:cshalizi/b:ba0d1c65f0ad/ [1906.05566] Hypotheses testing and posterior concentration rates for semi-Markov processes 2019-06-14T12:45:44+00:00 https://arxiv.org/abs/1906.05566 cshalizi to:NB stochastic_processes hypothesis_testing statistical_inference_for_stochastic_processes bayesian_consistency statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:44f148521a19/ Panel Data Analysis via Mechanistic Models: Journal of the American Statistical Association: Vol 0, No 0 2019-06-14T12:41:16+00:00 https://www.tandfonline.com/doi/full/10.1080/01621459.2019.1604367 cshalizi to:NB statistics statistical_inference_for_stochastic_processes time_series ionides.edward to_read particle_filters https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f0c8d0b86853/ [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/ Dahlhaus , Richter , Wu : Towards a general theory for nonlinear locally stationary processes 2019-05-25T03:02:16+00:00 https://projecteuclid.org/euclid.bj/1551862842 cshalizi to:NB stochastic_processes non-stationarity statistical_inference_for_stochastic_processes wu.wei-biao https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e1403d6f4c18/ 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/ McGoff , Mukherjee , Pillai : Statistical inference for dynamical systems: A review 2019-05-25T02:31:11+00:00 https://projecteuclid.org/euclid.ssu/1447165229 cshalizi dynamical_systems statistical_inference_for_stochastic_processes stochastic_processes statistics re:almost_none re:stacs have_read in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:98dfc7d60875/ Applied stochastic differential equations 2019-05-14T15:49:04+00:00 https://www.cambridge.org/9781316649466 cshalizi to:NB books:noted stochastic_differential_equations stochastic_processes filtering time_series statistical_inference_for_stochastic_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:be7b53a609b6/ [1903.01608] Theoretical guarantees for sampling and inference in generative models with latent diffusions 2019-05-13T13:37:45+00:00 https://arxiv.org/abs/1903.01608 cshalizi to:NB stochastic_processes inference_to_latent_objects statistical_inference_for_stochastic_processes neural_networks variational_inference raginsky.maxim have_skimmed re:almost_none control_theory_and_control_engineering https://pinboard.in/ https://pinboard.in/u:cshalizi/b:7cb225a6e2fa/ Extremes and Recurrence in Dynamical Systems | Wiley Online Books 2019-01-07T17:18:43+00:00 https://onlinelibrary.wiley.com/doi/book/10.1002/9781118632321 cshalizi to:NB books:noted extreme_values dynamical_systems time_series statistical_inference_for_stochastic_processes statistics downloaded recurrence_times https://pinboard.in/ 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