Results 11 to 20 of about 149,758 (276)

Approximate Bayesian Computation Using Indirect Inference [PDF]

Journal of the Royal Statistical Society Series C: Applied Statistics, 2011
SummaryWe present a novel approach for developing summary statistics for use in approximate Bayesian computation (ABC) algorithms by using indirect inference. ABC methods are useful for posterior inference in the presence of an intractable likelihood function.
Drovandi, Chris, Pettitt, Tony, Faddy, Malcolm   +2 more
openaire   +4 more sources

Non-linear regression models for Approximate Bayesian Computation

Statistics and Computing, 2009
Approximate Bayesian inference on the basis of summary statistics is well-suited to complex problems for which the likelihood is either mathematically or computationally intractable.
A. Butler, A. Gelman, B. Schölkopf, B.D. Ripley, C. Gourieroux, C.M. Bishop, C.P. Robert, D.A. Nix, D.E. Reich, E.A. Nadaraya, G. Weiss, G.E.P. Box, G.S. Watson, I.J. Wilson, J. Fan, J. Hey, J.H. Friedman, J.K. Pritchard, J.K. Pritchard, J.P. King, J.S. Liu, K. Heggland, L.A. Zhivotovsky, L.A. Zhivotovsky, M. Stephens, M. Tanaka, M.A. Beaumont, M.D. Shriver, M.K. Kuhner, N.J.R. Fagundes, O. Ratmann, P. Bortot, P. Marjoram, P. Marjoram, P.J. Diggle, S. Tavaré, S. Tavaré, S.A. Sisson, T. Ohta, T. Toni, V.N. Vapnik, W. Härdle, Y.-X. Fu, Y.-X. Fu   +43 more
core   +3 more sources

Extended Variational Message Passing for Automated Approximate Bayesian Inference. [PDF]

Entropy (Basel), 2021
Variational Message Passing (VMP) provides an automatable and efficient algorithmic framework for approximating Bayesian inference in factorized probabilistic models that consist of conjugate exponential family distributions.
Akbayrak S, Bocharov I, de Vries B.
europepmc   +2 more sources

An Approximate Bayesian Inference for Beta Regression Models [PDF]

Journal of Sciences, Islamic Republic of Iran, 2022
In modeling the variables related to each other, regression models are usually used assuming that the response variable is Normal. But in problems dealing with data such as the rate or ratio of an event distributed in the (0,1) interval, these models may
kobra Gholizadeh Gazvar, Mohsen Mohammadzadeh   +1 more
doaj   +1 more source

New Frontiers in Bayesian Modeling Using the INLA Package in R

Journal of Statistical Software, 2021
The INLA package provides a tool for computationally efficient Bayesian modeling and inference for various widely used models, more formally the class of latent Gaussian models.
Janet Van Niekerk, Haakon Bakka, Håvard Rue, Olaf Schenk   +3 more
doaj   +1 more source

Bayesian parameter inference and model selection by population annealing in systems biology. [PDF]

PLoS ONE, 2014
Parameter inference and model selection are very important for mathematical modeling in systems biology. Bayesian statistics can be used to conduct both parameter inference and model selection.
Yohei Murakami
doaj   +1 more source

Software for Bayesian Statistics

Journal of Statistical Software, 2021
In this summary we introduce the papers published in the special issue on Bayesian statistics. This special issue comprises 20 papers on Bayesian statistics and Bayesian inference on different topics such as general packages for hierarchical linear model
Michela Cameletti, Virgilio Gómez-Rubio
doaj   +1 more source

Demographic inference through approximate-Bayesian-computation skyline plots [PDF]

PeerJ, 2017
The skyline plot is a graphical representation of historical effective population sizes as a function of time. Past population sizes for these plots are estimated from genetic data, without a priori assumptions on the mathematical function defining the ...
Miguel Navascués, Raphaël Leblois, Concetta Burgarella   +2 more
doaj   +2 more sources

Bias-Corrected Maximum Likelihood Estimation and Bayesian Inference for the Process Performance Index Using Inverse Gaussian Distribution

Stats, 2022
In this study, the estimation methods of bias-corrected maximum likelihood (BCML), bootstrap BCML (B-BCML) and Bayesian using Jeffrey’s prior distribution were proposed for the inverse Gaussian distribution with small sample cases to obtain the ML and ...
Tzong-Ru Tsai, Hua Xin, Ya-Yen Fan, Yuhlong Lio   +3 more
doaj   +1 more source

Time Series of Counts under Censoring: A Bayesian Approach

Entropy, 2023
Censored data are frequently found in diverse fields including environmental monitoring, medicine, economics and social sciences. Censoring occurs when observations are available only for a restricted range, e.g., due to a detection limit.
Isabel Silva, Maria Eduarda Silva, Isabel Pereira, Brendan McCabe   +3 more
doaj   +1 more source