Zobrazeno 1 - 10
of 189
pro vyhledávání: '"Griffin, J E"'
Linear mixed effects models are widely used in statistical modelling. We consider a mixed effects model with Bayesian variable selection in the random effects using spike-and-slab priors and developed a variational Bayes inference scheme that can be
Externí odkaz:
http://arxiv.org/abs/2408.07365
Athletic performance follows a typical pattern of improvement and decline during a career. This pattern is also often observed within-seasons as athlete aims for their performance to peak at key events such as the Olympic Games or World Championships
Externí odkaz:
http://arxiv.org/abs/2405.17214
Autor:
Griffin, J. E.
Modern regression applications can involve hundreds or thousands of variables which motivates the use of variable selection methods. Bayesian variable selection defines a posterior distribution on the possible subsets of the variables (which are usua
Externí odkaz:
http://arxiv.org/abs/2402.12323
Publikováno v:
Journal of the Royal Statistical Society. Series B (Statistical Methodology), 2013 Jun 01. 75(3), 499-529.
Externí odkaz:
https://www.jstor.org/stable/24772735
Autor:
GRIFFIN, J. E., BROWN, P. J.
Publikováno v:
Biometrika, 2012 Jun 01. 99(2), 481-487.
Externí odkaz:
https://www.jstor.org/stable/41720705
Autor:
Griffin, J. E.
Publikováno v:
Journal of Productivity Analysis, 2011 Dec 01. 36(3), 275-283.
Externí odkaz:
https://www.jstor.org/stable/23883803
Autor:
Griffin, J. E., Steel, M. F. J.
Publikováno v:
Statistica Sinica, 2010 Oct 01. 20(4), 1507-1527.
Externí odkaz:
https://www.jstor.org/stable/24309513
Autor:
Griffin, J. E., Steel, M. F. J.
Publikováno v:
Journal of Productivity Analysis, 2008 Feb 01. 29(1), 33-50.
Externí odkaz:
https://www.jstor.org/stable/41770291
Autor:
Griffin, J. E., Steel, M. F. J.
Publikováno v:
Journal of the American Statistical Association, 2006 Mar 01. 101(473), 179-194.
Externí odkaz:
https://www.jstor.org/stable/30047448
Autor:
Griffin, J. E., Mitrodima, G.
We consider jointly modelling a finite collection of quantiles over time. Formal Bayesian inference on quantiles is challenging since we need access to both the quantile function and the likelihood. We propose a flexible Bayesian time-varying transfo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ff18a8f999693bfa8896d73e94a8cdd0