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Communications in Statistics - Simulation and Computation Volume 28, 1999 - Issue 4
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Original Articles

On markov chain monte carlo methods for nonlinear and non-gaussian state-space models

John Geweke Department of Economics, University of Minnesota and Federal Reserve Bank of Minneapolis, 1035 Management and Economics 271 - 19th Ave. S., Minneapolis, MN 55455, USA E-mail: [email protected]
&
Hisashi Tanizaki Faculty of Economics, Kobe University, Rokkodai, Nadaku, Kobe, 657-8501, Japan E-mail: [email protected]
Pages 867-894 | Received 01 Apr 1999, Published online: 27 Jun 2007

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Jarad Niemi & Mike West. (2010) Adaptive Mixture Modeling Metropolis Methods for Bayesian Analysis of Nonlinear State-Space Models. Journal of Computational and Graphical Statistics 19:2, pages 260-280.
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FABIOH. NIETO. (2005) Modeling Bivariate Threshold Autoregressive Processes in the Presence of Missing Data. Communications in Statistics - Theory and Methods 34:4, pages 905-930.
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John Geweke & Hisashi Tanizaki. (2003) Note on the Sampling Distribution for the Metropolis-Hastings Algorithm. Communications in Statistics - Theory and Methods 32:4, pages 775-789.
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Hisashi Tanizaki. (2000) Nonlinear and non-gaussian state estimation: A quasi-optimal estimator. Communications in Statistics - Theory and Methods 29:12, pages 2805-2834.
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Amane Saito & Hisashi Tanizaki. (2024) Volatility and returns of ESG indices: evidence from Japan. SN Business & Economics 4:3.
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Alexander Kreuzer, Luciana Dalla Valle & Claudia Czado. (2023) Bayesian multivariate nonlinear state space copula models. Computational Statistics & Data Analysis 188, pages 107820.
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Andreas Fichtner, Andrea Zunino, Lars Gebraad & Christian Boehm. (2021) Autotuning Hamiltonian Monte Carlo for efficient generalized nullspace exploration. Geophysical Journal International 227:2, pages 941-968.
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Jian He, Asma Khedher & Peter Spreij. (2021) A Kalman particle filter for online parameter estimation with applications to affine models. Statistical Inference for Stochastic Processes 24:2, pages 353-403.
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Zeyu Zhao & Mrinal K. Sen. (2021) A gradient-based Markov chain Monte Carlo method for full-waveform inversion and uncertainty analysis. GEOPHYSICS 86:1, pages R15-R30.
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David Luengo, Luca Martino, Mónica Bugallo, Víctor Elvira & Simo Särkkä. (2020) A survey of Monte Carlo methods for parameter estimation. EURASIP Journal on Advances in Signal Processing 2020:1.
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Leen Alawieh, Jonathan Goodman & John B. Bell. (2020) Iterative construction of Gaussian process surrogate models for Bayesian inference. Journal of Statistical Planning and Inference 207, pages 55-72.
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Pierre Thijssen & Sillas Hadjiloucas. 2020. State Estimation in Chemometrics. State Estimation in Chemometrics 213 257 .
Angela Bitto & Sylvia Frühwirth-Schnatter. (2019) Achieving shrinkage in a time-varying parameter model framework. Journal of Econometrics 210:1, pages 75-97.
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Andreas Mang, Amir Gholami, Christos Davatzikos & George Biros. (2018) PDE-constrained optimization in medical image analysis. Optimization and Engineering 19:3, pages 765-812.
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Tore Selland Kleppe. (2017) Modified Cholesky Riemann Manifold Hamiltonian Monte Carlo: exploiting sparsity for fast sampling of high-dimensional targets. Statistics and Computing 28:4, pages 795-817.
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Mamatha Venugopal, Ram Mohan Vasu & Debasish Roy. (2016) An Ensemble Kushner-Stratonovich-Poisson Filter for Recursive Estimation in Nonlinear Dynamical Systems. IEEE Transactions on Automatic Control 61:3, pages 823-828.
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S. Sarkar, S.R. Chowdhury, M. Venugopal, R.M. Vasu & D. Roy. (2014) A Kushner–Stratonovich Monte Carlo filter applied to nonlinear dynamical system identification. Physica D: Nonlinear Phenomena 270, pages 46-59.
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Noemi Petra, James Martin, Georg Stadler & Omar Ghattas. (2014) A Computational Framework for Infinite-Dimensional Bayesian Inverse Problems, Part II: Stochastic Newton MCMC with Application to Ice Sheet Flow Inverse Problems. SIAM Journal on Scientific Computing 36:4, pages A1525-A1555.
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Jonathan Briggs, Michael Dowd & Renate Meyer. (2013) Data assimilation for large‐scale spatio‐temporal systems using a location particle smoother. Environmetrics 24:2, pages 81-97.
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James Martin, Lucas C. Wilcox, Carsten Burstedde & Omar Ghattas. (2012) A Stochastic Newton MCMC Method for Large-Scale Statistical Inverse Problems with Application to Seismic Inversion. SIAM Journal on Scientific Computing 34:3, pages A1460-A1487.
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Phillip M. Yelland. (2009) Bayesian forecasting for low-count time series using state-space models: An empirical evaluation for inventory management. International Journal of Production Economics 118:1, pages 95-103.
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Hisashi Tanizaki & Shigeyuki Hamori. (2008) Volatility transmission between Japan, UK and USA in daily stock returns. Empirical Economics 36:1, pages 27-54.
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Mike K. P. So. (2006) Bayesian analysis of nonlinear and non-Gaussian state space models via multiple-try sampling methods. Statistics and Computing 16:2, pages 125-141.
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Hisashi Tanizaki. 2004. Computational Methods in Statistics and Econometrics. Computational Methods in Statistics and Econometrics.
Hisashi Tanizaki. 2004. Computational Methods in Statistics and Econometrics. Computational Methods in Statistics and Econometrics.
Hisashi Tanizaki. (2004) On Asymmetry, Holiday and Day-of-the-week Effects in Volatility of Daily Stock Returns: The Case of Japan. JOURNAL OF THE JAPAN STATISTICAL SOCIETY 34:2, pages 129-152.
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Hisashi Tanizaki. 2003. Stochastic Processes: Modelling and Simulation. Stochastic Processes: Modelling and Simulation 871 929 .
John Geweke & Hisashi Tanizaki. (2001) Bayesian estimation of state-space models using the Metropolis–Hastings algorithm within Gibbs sampling. Computational Statistics & Data Analysis 37:2, pages 151-170.
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Hisashi Tanizaki. (2001) Estimation of unknown parameters in nonlinear and non-Gaussian state-space models. Journal of Statistical Planning and Inference 96:2, pages 301-323.
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A. Chiuso & S. Soatto. (2000) Monte Carlo filtering on Lie groups. Monte Carlo filtering on Lie groups.
Jesús Fernández-Villaverde & Juan Francisco Rubio-Ramirez. (2004) Estimating Nonlinear Dynamic Equilibrium Economies: A Likelihood Approach. SSRN Electronic Journal.
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