Computational Statistics in Data Science - Группа авторов

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and Hobert, J.P. (2004) Sufficient burn‐in for Gibbs samplers for a hierarchical random effects model. Ann. Stat., 32, 784–817.

      37 37 Gupta, K. and Vats, D. (2020) Estimating Monte Carlo variance from multiple Markov chains. arXiv preprint arXiv:2007.04229.

      38 38 Dawkins, B. (1991) Siobhan's problem: the coupon collector revisited. Am. Stat., 45 (1), 76–82.

      39 39 Marske, D.M. (1967) BOD Data Interpretation Using the Sum of Squares Surface, University of Wisconsin, Madison.

      40 40 Bates, D.M. and Watts, D.G. (1988) Nonlinear Regression Analysis and Its Applications, vol. 2, Wiley, New York.

      41 41 Newton, M.A. and Raftery, A.E. (1994) Approximate Bayesian inference with the weighted likelihood bootstrap. J. R. Stat. Soc., Ser. B, 56, 3–26.

      42 42 Archila, F.H.A. (2016) Markov chain Monte Carlo for linear mixed models. PhD thesis. University of Minnesota.

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