Results 221 to 230 of about 1,788,159 (256)

Data-dependent probability matching priors of the second order

Statistics, 2009
We consider second-order probability matching priors that ensure frequentist validity of posterior quantiles with margin of error o(n −1), where n is the sample size. It is well known that there are many models of interest where data-free second-order probability matching priors do not exist.
S. H. Ong, Rahul Mukerjee
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Second-order matching prior family parametrized by sample size and matching probability

Statistical Papers, 2018
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Tanaka, Toyoto, Hirose, Yoshihiro, Komaki, Fumiyasu   +2 more
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Probability Matching Priors For One-Way Unbalanced Random Effect Models

Statistics & Risk Modeling, 2002
Summary: This paper considers development of noninformative priors for unbalanced one-way random effect models when the parameter of interest is the ratio of variance components. Several priors, including the Jeffreys prior, the two-group reference prior of \textit{J. M. Bernardo} [J. R. Stat. Soc., Ser.
Datta, Gauri Sankar, Ghosh, Malay, Kim, Yeong-Hwa   +2 more
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Probability matching priors for non-regular cases

Biometrika, 1999
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Probability matching priors for predicting unobservable random effects with application to ANOVA models

Statistics & Probability Letters, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chang, In Hong, Kim, Byung Hwee, Mukerjee, Rahul   +2 more
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Tracking Objects Using Density Matching and Shape Priors

, 2003
We present a novel method for tracking objects by combining density matching with shape priors. Density matching is a tracking method which operates by maximizing the Bhattacharyya similarity measure between the photometric distribution from an estimated
Freedman, Tao Zhang, Daniel Freedman
exaly   +2 more sources

Probability matching priors for predicting a dependent variable with application to regression models

Annals of the Institute of Statistical Mathematics, 2003
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Datta, Gauri Sankar, Mukerjee, Rahul
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Reference and probability‐matching priors in Bayesian analysis of mixed linear models

Journal of Animal Breeding and Genetics, 2002
SummaryDetermination of reasonable non‐informative priors in multiparameter problems is not easy; common non‐informative priors, such as Jeffrey's prior, can have features that have an unexpectedly dramatic effect on the posterior. In recognition of this problem Berger and Bernardo (Bayesian Statistics IV. Oxford University Press, Oxford, UK, pp. 35–70,
A. L. Pretorius, A. J. Van Der Merwe
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Data-dependent probability matching priors for likelihood ratio and adjusted likelihood ratio statistics

Statistics, 2013
We consider likelihood ratio statistics based on the usual profile likelihood and the standard adjustments thereof proposed in the literature in the presence of nuisance parameters. The role of data-dependent priors in ensuring approximate frequentist validity of posterior credible regions based on the inversion of these statistics is investigated ...
In Hong Chang, Rahul Mukerjee
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Using Bayesian Model Probability for Ranking Different Prior Scenarios in Reservoir History Matching

SPE Journal, 2019
Summary This paper considers Bayesian methods to discriminate between models depending on posterior model probability. When applying ensemble-based methods for model updating or history matching, the uncertainties in the parameters are typically assumed to be univariate Gaussian random fields.
Sigurd Ivar Aanonsen, Svenn Tveit, Mathias Alerini   +2 more
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