Relevant states and memory in Markov chain bootstrapping and simulation
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[1] Joseph P. Romano,et al. The stationary bootstrap , 1994 .
[2] Meir Feder,et al. A universal finite memory source , 1995, IEEE Trans. Inf. Theory.
[3] Soumendra N. Lahiri,et al. A nonparametric plug-in rule for selecting optimal block lengths for block bootstrap methods ☆ , 2007 .
[4] H. White,et al. Data‐Snooping, Technical Trading Rule Performance, and the Bootstrap , 1999 .
[5] Efstathios Paparoditis,et al. The Tapered Block Bootstrap for General Statistics from Stationary Sequences , 2002 .
[6] M. B. Rajarshi. Bootstrap in Markov-sequences based on estimates of transition density , 1990 .
[7] F. Dufour,et al. Approximation of Markov decision processes with general state space , 2012 .
[8] Yuval Peres,et al. Two new Markov order estimators , 2005 .
[9] Abraham Lempel,et al. A sequential algorithm for the universal coding of finite memory sources , 1992, IEEE Trans. Inf. Theory.
[10] Countable state Markov process bootstrap , 1999 .
[11] Andrey L. Vasnev,et al. Markov chain approximation in bootstrapping autoregressions , 2002 .
[12] G. Schwarz. Estimating the Dimension of a Model , 1978 .
[13] A. Kolmogorov. Three approaches to the quantitative definition of information , 1968 .
[14] Joseph P. Romano,et al. A General Resampling Scheme for Triangular Arrays of $\alpha$-Mixing Random Variables with Application to the Problem of Spectral Density Estimation , 1992 .
[15] I. Csiszár,et al. The consistency of the BIC Markov order estimator , 2000 .
[16] Efstathios Paparoditis,et al. Tapered block bootstrap , 2001 .
[17] H. White,et al. Automatic Block-Length Selection for the Dependent Bootstrap , 2004 .
[18] Neri Merhav,et al. On the estimation of the order of a Markov chain and universal data compression , 1989, IEEE Trans. Inf. Theory.
[19] Carsten Hartmann,et al. Markov State Models for Rare Events in Molecular Dynamics , 2013, Entropy.
[20] JORMA RISSANEN,et al. A universal data compression system , 1983, IEEE Trans. Inf. Theory.
[21] Robert Tibshirani,et al. An Introduction to the Bootstrap CHAPMAN & HALL/CRC , 1993 .
[22] E. Carlstein. The Use of Subseries Values for Estimating the Variance of a General Statistic from a Stationary Sequence , 1986 .
[23] P. Hall,et al. On blocking rules for the bootstrap with dependent data , 1995 .
[24] Michael K. Ng,et al. Higher-order multivariate Markov chains and their applications , 2008 .
[25] John C. Kieffer,et al. Strongly consistent code-based identification and order estimation for constrained finite-state model classes , 1993, IEEE Trans. Inf. Theory.
[26] Robert Tibshirani,et al. Bootstrap Methods for Standard Errors, Confidence Intervals, and Other Measures of Statistical Accuracy , 1986 .
[27] Aurélien Garivier,et al. A minimum description length approach to hidden Markov models with Poisson and Gaussian emissions. Application to order identification , 2009 .
[28] D. White. Infinite horizon Markov decision processes with unknown or variable discount factors , 1987 .
[29] D. Freedman. On Bootstrapping Two-Stage Least-Squares Estimates in Stationary Linear Models , 1984 .
[30] J. Rissanen,et al. Modeling By Shortest Data Description* , 1978, Autom..
[31] Vijay S. Pande,et al. Everything you wanted to know about Markov State Models but were afraid to ask. , 2010, Methods.
[32] Robert Givan,et al. Equivalence notions and model minimization in Markov decision processes , 2003, Artif. Intell..
[33] P. Bühlmann,et al. Block length selection in the bootstrap for time series , 1999 .
[34] Alan David Hutson,et al. Resampling Methods for Dependent Data , 2004, Technometrics.
[35] Prakash Narayan,et al. Order estimation and sequential universal data compression of a hidden Markov source by the method of mixtures , 1994, IEEE Trans. Inf. Theory.
[36] Glen G. Langdon,et al. Universal modeling and coding , 1981, IEEE Trans. Inf. Theory.
[37] P. Bühlmann,et al. Variable Length Markov Chains: Methodology, Computing, and Software , 2004 .
[38] B. LeBaron,et al. Simple Technical Trading Rules and the Stochastic Properties of Stock Returns , 1992 .
[39] Scott Sanner,et al. Real-time dynamic programming for Markov decision processes with imprecise probabilities , 2016, Artif. Intell..
[40] David Hinkley,et al. Bootstrap Methods: Another Look at the Jackknife , 2008 .
[41] A. Ullah. Entropy, divergence and distance measures with econometric applications , 1996 .
[42] Regina Y. Liu. Moving blocks jackknife and bootstrap capture weak dependence , 1992 .
[43] M. Kenward,et al. An Introduction to the Bootstrap , 2007 .
[44] H. Künsch. The Jackknife and the Bootstrap for General Stationary Observations , 1989 .
[45] Pravin Varaiya,et al. Simulation-based optimization of Markov decision processes: An empirical process theory approach , 2010, Autom..
[46] Sung-Hyuk Cha. Comprehensive Survey on Distance/Similarity Measures between Probability Density Functions , 2007 .
[47] Takayoshi Tamura,et al. New approximate dynamic programming algorithms for large-scale undiscounted Markov decision processes and their application to optimize a production and distribution system , 2016, Eur. J. Oper. Res..
[48] Jorma Rissanen,et al. Complexity of strings in the class of Markov sources , 1986, IEEE Trans. Inf. Theory.
[49] Peter Bühlmann,et al. Sieve Bootstrap With Variable-Length Markov Chains for Stationary Categorical Time Series , 2002 .
[50] Gary H. Chao. Production and availability policies through the Markov Decision Process and myopic methods for contractual and selective orders , 2013, Eur. J. Oper. Res..
[51] Stanislav Anatolyev. Electoral behavior of US counties: a panel data approach , 2002 .
[52] J. Bernardo,et al. Bayesian Hypothesis Testing: a Reference Approach , 2002 .
[53] Efstathios Paparoditis,et al. A MARKOVIAN LOCAL RESAMPLING SCHEME FOR NONPARAMETRIC ESTIMATORS IN TIME SERIES ANALYSIS , 2001, Econometric Theory.
[54] Benjamin Weiss,et al. Order estimation of Markov chains , 2005, IEEE Transactions on Information Theory.
[55] Neri Merhav,et al. Estimating the number of states of a finite-state source , 1992, IEEE Trans. Inf. Theory.
[56] Prakasa Rao,et al. BOOTSTRAPPING A FINITE STATE MARKOV CHAIN , 2016 .
[57] Roy Cerqueti,et al. A Tabu Search heuristic procedure in Markov chain bootstrapping , 2013, Eur. J. Oper. Res..
[58] Jorma Rissanen,et al. The Minimum Description Length Principle in Coding and Modeling , 1998, IEEE Trans. Inf. Theory.
[59] D. Politis,et al. The local bootstrap for Markov processes , 2002 .
[60] W. McCormick,et al. Regeneration-based bootstrap for Markov chains , 1993 .
[61] P. Bühlmann. Sieve bootstrap for time series , 1997 .
[62] Neri Merhav,et al. Universal prediction of individual sequences , 1992, IEEE Trans. Inf. Theory.
[63] Hyeong Soo Chang,et al. On functional equations for Kth best policies in Markov decision processes , 2013, Autom..
[64] I. Basawa,et al. Asymptotic bootstrap validity for finite markov chains , 1990 .
[65] P. Bertail,et al. Second-order properties of regeneration-based bootstrap for atomic Markov chains , 2007 .
[66] K. Athreya,et al. Bootstrapping Markov chains: countable case , 1992 .
[67] U. Rieder,et al. Markov Decision Processes , 2010 .
[68] D. Freedman,et al. Bootstrapping a Regression Equation: Some Empirical Results , 1984 .
[69] Imre Csiszár. Large-scale typicality of Markov sample paths and consistency of MDL Order estimators , 2002, IEEE Trans. Inf. Theory.
[70] Joel L. Horowitz,et al. Bootstrap Methods for Markov Processes , 2003 .
[71] Dimitrios G. Pandelis. Markov decision processes with multidimensional action spaces , 2010, Eur. J. Oper. Res..
[72] P. Bertail,et al. Regenerative block bootstrap for Markov chains , 2006 .
[73] Peter Hall. Resampling a coverage pattern , 1985 .