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Modern computational advances have enabled easy parallel implementations of Markov chain Monte Carlo (MCMC).
An n-dimensional rosenbrock distribution for mcmc testing
Pagani, F., Wiegand, M., and Nadarajah, S. (2019) · 1903
Earlier work this paper cites.
An invariance principle for the law of the iterated logarithm
Strassen, V. (1964) · 1964
Earlier work this paper cites.
Multiple time series: Wiley series in probability and mathematical statistics
Hannan, E. J. (1970) · 1970
Earlier work this paper cites.
Multivariate estimation in regenerative simulation
Seila, A. F. (1982) · 1982
Earlier work this paper cites.
Multivariate inference in stationary simulation using batch means
Chen, D.-F. R. and Seila, A. F. (1987) · 1987
Earlier work this paper cites.
Heteroskedasticity and autocorrelation consistent covariance matrix estimation
Andrews, D. W. (1991) · 1991
Earlier work this paper cites.
Estimating the asymptotic variance with batch means
Glynn, P. W. and Whitt, W. (1991) · 1991
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Inference from iterative simulation using multiple sequences (with discussion)
Gelman, A. and Rubin, D. B. (1992) · 1992
Earlier work this paper cites.
The asymptotic validity of sequential stopping rules for stochastic simulations
Glynn, P. W. and Whitt, W. (1992) · 1992
Earlier work this paper cites.
Mean-square consistency of the variance estimator in steady-state simulation output analysis
Damerdji, H. (1995) · 1995
Earlier work this paper cites.
Conditioning in Markov chain Monte Carlo
Geyer, C. J. (1995) · 1995
Earlier work this paper cites.
Optimal mean-squared-error batch sizes
Song, W. T. and Schmeiser, B. W. (1995) · 1995
Earlier work this paper cites.
Rate of convergence of the Gibbs sampler by Gaussian approximation
Roberts, G. O. and Sahu, S. K. (1996) · 1996
Earlier work this paper cites.
General methods for monitoring convergence of iterative simulations
Brooks, S. P. and Gelman, A. (1998) · 1998
Earlier work this paper cites.
Convergence assessment techniques for Markov chain Monte Carlo
Brooks, S. P. and Roberts, G. O. (1998) · 1998
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Markov chain Monte Carlo in practice: a roundtable discussion
Kass, R. E., Carlin, B. P., Gelman, A., and Neal, R. M. (1998) · 1998
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Monte Carlo error estimation for multivariate Markov chains
Kosorok, M. R. (2000) · 2000
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On the Markov chain central limit theorem
Jones, G. L. (2004) · 2004
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Replicated batch means for steady-state simulations
Argon, N. T. and Andradóttir, S. (2006) · 2006
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Fixed-width output analysis for Markov chain Monte Carlo
Jones, G. L., Haran, M., Caffo, B. S., and Neath, R. (2006) · 2006
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Convergence diagnostics for Markov chain Monte Carlo
Roy, V. (2019) · 2019
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Multivariate output analysis for Markov chain Monte Carlo
Vats, D., Flegal, J. M., and Jones, G. L. (2019) · 2019
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palmerpenguins: Palmer Archipelago (Antarctica) penguin data
Horst, A. M., Hill, A. P., and Gorman, K. B. (2020) · 2020
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Analyzing Markov chain Monte Carlo output
Vats, D., Robertson, N., Flegal, J. M., and Jones, G. L. (2020) · 2020
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Rank-normalization, folding, and localization: An improved R ^ \widehat{R} for assessing convergence of MCMC
Vehtari, A., Gelman, A., Simpson, D., Carpenter, B., and Bürkner, P.-C. (2020) · 2020
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Batch size selection for variance estimators in mcmc
Liu, Y., Vats, D., and Flegal, J. M. (2021) · 2021
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Zeidler, E. (2013) · 2007
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Markov chain Monte Carlo: Can we trust the third significant figure?
Flegal, J. M., Haran, M., and Jones, G. L. (2008) · 2008
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Batch means and spectral variance estimators in Markov chain Monte Carlo
Flegal, J. M. and Jones, G. L. (2010) · 2010
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Ensemble samplers with affine invariance
Goodman, J. and Weare, J. (2010) · 2010
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A practical sequential stopping rule for high-dimensional Markov chain Monte Carlo
Gong, L. and Flegal, J. M. (2016) · 2016
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Multivariate initial sequence estimators in Markov chain Monte Carlo
Dai, N. and Jones, G. L. (2017) · 2017
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Revisiting the Gelman–Rubin diagnostic
Vats, D. and Knudson, C. (2021) · 2021
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Globally centered autocovariances in MCMC
Agarwal, M. and Vats, D. (2022) · 2022
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Estimating accuracy of the MCMC variance estimator: Asymptotic normality for batch means estimators
Chakraborty, S., Bhattacharya, S. K., and Khare, K. (2022) · 2022
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Challenges in Markov chain Monte Carlo for Bayesian neural networks
Papamarkou, T., Hinkle, J., Young, M. T., and Womble, D. (2022) · 2022
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Lugsail lag windows for estimating time-average covariance matrices
Vats, D. and Flegal, J. M. (2022) · 2022
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Efficient shape-constrained inference for the autocovariance sequence from a reversible markov chain
Berg, S. and Song, H. (2023) · 2023
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Multivariate strong invariance principles in markov chain monte carlo
Banerjee, A. and Vats, D. (2024) · 2024
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