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MaCh3 2.2.1
Reference Guide
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Carlos A. Argüelles, Austin Schneider, and Tianlu Yuan. A binned likelihood for stochastic models. JHEP, 06:030, 2019.
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Saptarshi Chakraborty, Suman K. Bhattacharya, and Kshitij Khare. Estimating accuracy of the MCMC variance estimator: a central limit theorem for batch means estimators, 2019.
J. S. Conway. Incorporating Nuisance Parameters in Likelihoods for Multisource Spectra. In PHYSTAT 2011, pages 115–120, 2011.
Hans Peter Dembinski and Ahmed Abdelmotteleb. A new maximum-likelihood method for template fits. Eur. Phys. J. C, 82(11):1043, 2022.
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Qijun Fang. A Brief Introduction to Geweke’s Diagnostics. https://math.arizona.edu/ piegorsch/675/GewekeDiagnostics.pdf, May 2014. STAT 675, University of Arizona.
Jonah Gabry and Martin Modrák. Visual MCMC diagnostics using the bayesplot package. https://mc-stan.org/bayesplot/articles/visual-mcmc-diagnostics.html, January 2024. Source: vignettes/visual-mcmc-diagnostics.Rmd.
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Andrew Gelman, Jessica Hwang, and Aki Vehtari. Understanding predictive information criteria for bayesian models. Statistics and Computing, 24(6):997–1016, 2014.
Heikki Haario, Eero Saksman, and Johanna Tamminen. An adaptive metropolis algorithm. Bernoulli, 7(2):223–242, April 2001.
Kenneth M. Hanson. Tutorial on Markov Chain Monte Carlo. Presented at the 29th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Technology, Gif-sur-Yvette, France, July 8–13, 2009, 2008. Revised 14/05/08, LA-UR-05-5680.
Florian Hartig. WAIC Calculation in BayesianTools Package, 2024. Accessed: 2024-11-30.
Fred James and Matthias Winkler. MINUIT User's Guide. June 2004.
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Jarle Karlsbakk. Likelihood Inference and Comparison of Time-Inhomogeneous Markov Processes. Master's thesis, Stockholm University, Department of Mathematics, 2011.
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Karl Pearson. X. on the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, 50(302):157–175, 1900.
William H. Press, Saul A. Teukolsky, William T. Vetterling, and Brian P. Flannery. Numerical Recipes in C: The Art of Scientific Computing. Cambridge University Press, second edition edition, 1992. William H. Press: Harvard-Smithsonian Center for Astrophysics, Saul A. Teukolsky: Department of Physics, Cornell University, William T. Vetterling: Polaroid Corporation, Brian P. Flannery: EXXON Research and Engineering Company.
Gareth O. Roberts and Jeffrey S. Rosenthal. Examples of Adaptive MCMC. Journal of Computational and Graphical Statistics, 18(2):349–367, 2009.
Manuel D. Rossetti. The Batch Means Method, 2024.
David J. Spiegelhalter, Nicola G. Best, Bradley P. Carlin, and Angelika Van Der Linde. Bayesian measures of model complexity and fit. Journal of the Royal Statistical Society Series B: Statistical Methodology, 64(4):583–639, October 2002.
Stan Development Team. Stan Reference Manual: Effective Sample Size, 2018. Version 2.18.
The BRugs Development Team. DIC Function: Deviance Information Criterion, 2024. Accessed: 2024-11-29.
Aki Vehtari, Andrew Gelman, Daniel Simpson, Bob Carpenter, and Paul-Christian Bürkner. Rank-normalization, folding, and localization: An improved widehat R for assessing convergence of MCMC.
M. Wang, W.J. Huang, F.G. Kondev, G. Audi, and S. Naimi. The AME 2020 atomic mass evaluation (II). Tables, graphs and references. Chinese Physics C, 34(3):030003, 2021.