Zobrazeno 1 - 10
of 122
pro vyhledávání: '"Bayarri M. J."'
Informally, "Information Inconsistency" is the property that has been observed in many Bayesian hypothesis testing and model selection procedures whereby the Bayesian conclusion does not become definitive when the data seems to become definitive. An
Externí odkaz:
http://arxiv.org/abs/1710.09700
Much of science is (rightly or wrongly) driven by hypothesis testing. Even in situations where the hypothesis testing paradigm is correct, the common practice of basing inferences solely on p-values has been under intense criticism for over 50 years.
Externí odkaz:
http://arxiv.org/abs/1512.08552
Publikováno v:
Annals of Statistics 2012, Vol. 40, No. 3, 1550-1577
In objective Bayesian model selection, no single criterion has emerged as dominant in defining objective prior distributions. Indeed, many criteria have been separately proposed and utilized to propose differing prior choices. We first formalize the
Externí odkaz:
http://arxiv.org/abs/1209.5240
Publikováno v:
IMS Collections 2008, Vol. 3, 105-121
The Poisson distribution is often used as a standard model for count data. Quite often, however, such data sets are not well fit by a Poisson model because they have more zeros than are compatible with this model. For these situations, a zero-inflate
Externí odkaz:
http://arxiv.org/abs/0805.3220
Autor:
Bayarri, M. J., Castellanos, M. E.
Publikováno v:
Statistical Science 2007, Vol. 22, No. 3, 363-367
Rejoinder: Bayesian Checking of the Second Levels of Hierarchical Models [arXiv:0802.0743]
Comment: Published in at http://dx.doi.org/10.1214/07-STS235REJ the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Stat
Comment: Published in at http://dx.doi.org/10.1214/07-STS235REJ the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Stat
Externí odkaz:
http://arxiv.org/abs/0802.0754
Autor:
Bayarri, M. J., Castellanos, M. E.
Publikováno v:
Statistical Science 2007, Vol. 22, No. 3, 322-343
Hierarchical models are increasingly used in many applications. Along with this increased use comes a desire to investigate whether the model is compatible with the observed data. Bayesian methods are well suited to eliminate the many (nuisance) para
Externí odkaz:
http://arxiv.org/abs/0802.0743
Autor:
Bayarri, M. J., García-Donato, G.
Publikováno v:
Journal of the Royal Statistical Society, Series B, (2008), vol. 70, pp. 981--1003
In this paper we introduce objective proper prior distributions for hypothesis testing and model selection based on measures of divergence between the competing models; we call them divergence based (DB) priors. DB priors have simple forms and desira
Externí odkaz:
http://arxiv.org/abs/0801.4224
Autor:
Bayarri, M. J., Berger, J. O., Cafeo, J., Garcia-Donato, G., Liu, F., Palomo, J., Parthasarathy, R. J., Paulo, R., Sacks, J., Walsh, D.
Publikováno v:
Annals of Statistics 2007, Vol. 35, No. 5, 1874-1906
A key question in evaluation of computer models is Does the computer model adequately represent reality? A six-step process for computer model validation is set out in Bayarri et al. [Technometrics 49 (2007) 138--154] (and briefly summarized below),
Externí odkaz:
http://arxiv.org/abs/0711.3271
Autor:
Bayarri, M. J., Berger, J. O.
Publikováno v:
Statistical Science, 2004 Feb 01. 19(1), 58-80.
Externí odkaz:
https://www.jstor.org/stable/4144373
Autor:
Bayarri, M. J., Mayoral, A. M.
Publikováno v:
The American Statistician, 2002 Aug 01. 56(3), 207-214.
Externí odkaz:
https://www.jstor.org/stable/3087300