Results 1 to 10 of about 109,308 (284)
The Bayes Estimators of the Variance and Scale Parameters of the Normal Model With a Known Mean for the Conjugate and Noninformative Priors Under Stein’s Loss [PDF]
Frontiers in Big Data, 2022 For the normal model with a known mean, the Bayes estimation of the variance parameter under the conjugate prior is studied in Lehmann and Casella (1998) and Mao and Tang (2012).
Ying-Ying Zhang +5 more
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A Geometric View of Conjugate Priors [PDF]
Machine Learning, 2010 16 pages, 4 ...
Arvind Agarwal, Hal Daumé
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Asymmetric Conjugate Priors for Large Bayesian VARs [PDF]
SSRN Electronic Journal, 2021 Large Bayesian VARs are now widely used in empirical macroeconomics. One popular shrinkage prior in this setting is the natural conjugate prior as it facilitates posterior simulation and leads to a range of useful analytical results. This is, however, at the expense of modeling flexibility, as it rules out cross‐variable shrinkage, that is, shrinking ...
Joshua C. C. Chan
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Calibrating the prior distribution for a normal model with conjugate prior. [PDF]
J Stat Comput Simul, 2014 For a normal model with a conjugate prior, we provide an in depth examination of the effects of the hyperparameters on the long-run frequentist properties of posterior point and interval estimates. Under an assumed sampling model for the data generating mechanism, we examine how hyperparameter values affect the mean squared error (MSE) of posterior ...
Alber SA, Lee JJ.
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Polysaccharide responsiveness is not biased by prior pneumococcal-conjugate vaccination. [PDF]
PLoS ONE, 2013 Polysaccharide responsiveness is tested by measuring antibody responses to polysaccharide vaccines to diagnose for humoral immunodeficiency. A common assumption is that this responsiveness is biased by any previous exposure to the polysaccharides in the ...
Jens Magnus Bernth-Jensen +1 more
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Conjugate Priors for Exponential Families [PDF]
The Annals of Statistics, 1979 Let $X$ be a random vector distributed according to an exponential family with natural parameter $\theta \in \Theta$. We characterize conjugate prior measures on $\Theta$ through the property of linear posterior expectation of the mean parameter of $X : E\{E(X|\theta)|X = x\} = ax + b$.
Persi Diaconis, Donald Ylvisaker
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Conjugate priors and bias reduction for logistic regression models
Statistics & Probability Letters, 2022 Logistic regression models for binomial responses are routinely used in statistical practice. However, the maximum likelihood estimate may not exist due to data separability. We address this issue by considering a conjugate prior penalty which always produces finite estimates.
Tommaso Rigon, Emanuele Aliverti
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Bayesian inference for Pareto distribution with prior conjugate and prior non conjugate [PDF]
Jurnal Matematika, Statistika dan Komputasi, 2020 The purpose of this study is to determine the best estimator for estimating the shape parameters of the Pareto distribution with the known scale parameter. Estimation of these parameters is done by using the Gamma distribution as the prior distribution of the conjugate and the Uniform distribution as the non-conjugate prior distribution.
Ferra Yanuar, Cici Saputri
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Bayesian Analysis of Occupational Exposure Data with Conjugate Priors [PDF]
Annals of Work Exposures and Health, 2017 Bayesian analysis is a flexible method that can yield insight into occupational exposures as the methods quantify plausible values for exposure parameters of interest, such as the mean, variance, and specific percentiles of the exposure distribution. We describe three Bayesian analysis methods for the analysis of normally distributed data (e.g.
Rachael M. Jones, Igor Burstyn
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Enriched conjugate and reference priors for the Wishart family on symmetric cones [PDF]
The Annals of Statistics, 2003 A general Wishart family on a symmetric cone is a natural exponential family (NEF) having a homogeneous quadratic variance function. Using results in the abstract theory of Euclidean Jordan algebras, the structure of conditional reducibility is shown to hold for such a family, and we identify the associated parameterization $\phi$ and analyze its ...
Guido Consonni, Piero Veronese
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