The Selection of Prior Distributions by Formal Rules

From MaRDI portal
Publication:4366032

DOI10.2307/2291752zbMath0884.62007OpenAlexW4239683439MaRDI QIDQ4366032

Robert E. Kass, Larry Alan Wasserman

Publication date: 22 March 1998

Full work available at URL: https://doi.org/10.2307/2291752



Related Items

Single observation unbiased priors, Overall objective priors, Partial information reference priors: Derivation and interpretations, Some aspects of the history of Bayesian information processing, Modeling body height in prehistory using a spatio-temporal Bayesian errors-in-variables model, A defence of subjective fiducial inference, Stimulus reference frame and neural coding precision, An unsupervised machine-learning checkpoint-restart algorithm using Gaussian mixtures for particle-in-cell simulations, Bayesian multiple change-points estimation for hazard with censored survival data from exponential distributions, Statistical analysis of composite spectra, Bayesian frequentist hybrid inference, Bayesian tests of symmetry for the generalized von Mises distribution, Prior distributions for objective Bayesian analysis, On universal prediction and Bayesian confirmation, Neglected chaos in international stock markets: Bayesian analysis of the joint return-volatility dynamical system, Prediction markets, Bayesian priors, and clinical trials, Bayesian model learning based on predictive entropy, A Bayesian approach to the analysis of asymmetric association for two-way contingency tables, A note on noninformative priors for Weibull distributions., Open problems in universal induction \& intelligence, Objective priors for the number of degrees of freedom of a multivariate \(t\) distribution and the \(t\)-copula, Structured hierarchical models for probabilistic inference from perturbation screening data, Relative entropy and envy-free allocation, The potential and perils of preprocessing: building new foundations, Analytical derivation of the reference prior by sequential maximization of Shannon's mutual information in the multi-group parameter case, An objective Bayesian estimation of parameters in a log-binomial model, A decision-theoretical view of default priors, Evaluating default priors with a generalization of Eaton's Markov chain, Bayesian graphical model determination using decision theory, Blending Bayesian and frequentist methods according to the precision of prior information with applications to hypothesis testing, Bayesian inference and the parametric bootstrap, A data cloning algorithm for computing maximum likelihood estimates in spatial generalized linear mixed models, Harold Jeffreys's \textit{Theory of probability} revisited, Bayes, Jeffreys, prior distributions and the philosophy of statistics, Comment: The importance of Jeffreys's legacy, Combining independent Bayesian posteriors into a confidence distribution, with application to estimating climate sensitivity, Constructing informative model priors using hierarchical methods, A general divergence criterion for prior selection, Reference priors for linear models with general covariance structures, Objective Bayesian analysis for the normal compositional model, Hierarchical Bayes, maximum a posteriori estimators, and minimax concave penalized likelihood estimation, A review of Bayesian asymptotics in general insurance applications, Objective priors: an introduction for frequentists, Discussion on ``Objective priors: an introduction for frequentists by M. Ghosh, On probabilistic parametric inference, Eliciting vague but proper maximal entropy priors in Bayesian experiments, Reference priors for the general location-scale model, Posterior properties of the Weibull distribution for censored data, Optimal designs for nonlinear regression models with respect to non-informative priors, Reference priors for non-normal two-sample problems, Solving operational statistics via a Bayesian analysis, Bayesian analysis of vector-autoregressive models with noninformative priors., Enriched conjugate and reference priors for the Wishart family on symmetric cones, Mixing time of exponential random graphs, Assessing model mimicry using the parametric bootstrap., Power prior distributions for generalized linear models, Objective Bayesianism with predicate languages, An introduction to the Bayes information criterion: theoretical foundations and interpretation, Objective Bayesian analysis of geometrically anisotropic spatial data, General frequentist properties of the posterior profile distribution, Bayesian model selection and model averaging, The importance of complexity in model selection, Infinitesimal distributions, improper priors and Bayesian inference, A geometric principle of indifference, Evaluation of formal posterior distributions via Markov chain arguments, Analysis of comparative data with hierarchical autocorrelation, Finite-sample investigation of likelihood and Bayes inference for the symmetric von Mises-Fisher distribution, Limits of learning about a categorical latent variable under prior near-ignorance, Reuse, recycle, reweigh: combating influenza through efficient sequential Bayesian computation for massive data, Beta-MPT: multinomial processing tree models for addressing individual differences, Objective Bayesian analysis of accelerated competing failure models under type-I censoring, Statistical models: conventional, penalized and hierarchical likelihood, Bayesian and likelihood-based inference for the bivariate normal correlation coefficient, Bayesian variable selection using cost-adjusted BIC, with application to cost-effective measurement of quality of health care, Asymptotic equivalence between frequentist and Bayesian prediction limits for the Poisson distribution, Asymptotics of Bayesian median loss estimation, Penalising model component complexity: a principled, practical approach to constructing priors, How principled and practical are penalised complexity priors?, A weakly informative default prior distribution for logistic and other regression models, We are all Bayesian, everyone is not a Bayesian, Bayesian copula selection, Biased information and the exchange paradox, Noninformative priors and frequentist risks of Bayesian estimators of vector-autoregressive models, Charles Stein and invariance: beginning with the Hunt-Stein theorem, An explanatory rationale for priors sharpened into Occam's razors, On a class of objective priors from scoring rules (with discussion), A model selection approach for variable selection with censored data, On defining ex ante payoffs in games with diffuse prior, Approximate large-scale Bayesian spatial modeling with application to quantitative magnetic resonance imaging, A conversation with Robert E. Kass, On a prior based on the Wasserstein information matrix, Bayesian approach for confidence intervals of variance on the normal distribution, Intrinsic Bayes factor approach to a test for the power law process., Resolvable block designs for factorial experiments., On estimating the current intensity of failure for the power-law process, Bayesian \(A\)-optimal two-phase designs with a single blocking factor in each phase, On the complexity of additive clustering models, Strong matching of frequentist and Bayesian parametric inference, What is meant by ``missing at random?, A new bivariate exponential distribution for modeling moderately negative dependence, Characterizing Dirichlet Priors, A new approach to default priors and robust bayes methodology, Sensitivity of Bayes Estimators to Hyper-Parameters with an Application to Maximum Yield from Fisheries, Model averages sharpened into Occam’s razors: Deep learning enhanced by Rényi entropy, A Proposal for Informative Default Priors Scaled by the Standard Error of Estimates, Assessing process capability based on Bayesian approach with subsamples, An introduction to the imprecise Dirichlet model for multinomial data, Bayesian analysis of the inverse generalized gamma distribution using objective priors, Bayesian-motivated tests of function fit and their asymptotic frequentist properties, Default priors for Gaussioan processes, Invariant Bayesian estimation on manifolds, BayesianP-Values for Testing Independence in 2 × 2 Contingency Tables, I Got More Data, My Model is More Refined, but My Estimator is Getting Worse! Am I Just Dumb?, Objective Frequentist Uncertainty Quantification for Atmospheric \(\mathrm{CO}_2\) Retrievals, Using experimental data and information criteria to guide model selection for reaction-diffusion problems in mathematical biology, A class of flat prior distributions for the Poisson‐gamma hierarchical model, Drug sensitivity prediction with normal inverse Gaussian shrinkage informed by external data, Objective Bayesian approach to the Jeffreys-Lindley paradox, A Bayesian spatial voting model to characterize the legislative behavior of the Colombian Senate 2010–2014, Calibrated Bayes factors under flexible priors, Power Laws Distributions in Objective Priors, Reference Priors for the Generalized Extreme Value Distribution, Unnamed Item, Global robust Bayesian analysis in large models, Quantifying observed prior impact, On posterior consistency of Bayesian factor models in high dimensions, Large-Scale Bayesian Spatial-Temporal Regression with Application to Cardiac MR-Perfusion Imaging, Assessment of generalised Bayesian structural equation models for continuous and binary data, Neyman–Pearson lemma for Bayes factors, A heteroscedastic Bayesian model for method comparison data, CBM for testing multiple hypotheses with directional alternatives in sequential experiments, Invariance of posterior distributions under reparametrization, On the Flatland paradox and limiting arguments, Having a look at the Bayes blind spot, Ambiguity and the Bayesian Paradigm, A tutorial on adaptive design optimization, Bayesian approach to the inverse problem in a light scattering application, Asymptotics of Posteriors for Binary Branching Processes, Randomized Projection for Rank-Revealing Matrix Factorizations and Low-Rank Approximations, Assessing the relevance of an information source to trading from an adaptive-markets hypothesis perspective, Optimal error regions for quantum state estimation, Monte Carlo sampling from the quantum state space. I, Posterior distribution for negative binomial parameter \(p\) using a group invariant prior, The Current Position of Statistics: A Personal View, Functional Uniform Priors for Nonlinear Modeling, R. A. Fisher in the 21st century. Invited paper presented at the 1996 R. A. Fisher lecture. (With comments)., A 250-year argument: Belief, behavior, and the bootstrap, A Bayesian approach to testing decision making axioms, Nonconjugate Bayesian Analysis of Variance Component Models, Comparison of testing procedures utilizingP-values and Bayes factors in some common situations, Nonparametric goodness-of-fit, Bayesian equivalence testing for binomial random variables, An Objective Bayesian Approach to Multistage Hypothesis Testing, Bayesian Estimation of the Size of a Closed Population Using Photo-ID Data with Part of the Population Uncatchable, A solution to separation for clustered binary data, Objective priors for hypothesis testing in one‐way random effects models, A Hybrid Approximation Bayesian Test of Variance Components for Longitudinal Data, Jeffreys priors for survival models with censored data, An alternative approach to test process capability for unilateral specification with subsamples, Modeling individual differences using Dirichlet processes, Model selection for the rate problem: a comparison of significance testing, Bayesian and minimum description length statistical inference, Imprecise probability models for learning multinomial distributions from data. Applications to learning credal networks, A Bayesian Model for Markov Chains via Jeffrey's Prior, Noninformative priors for the common mean in the bivariate normal distribution, Non-informative priors for the common mean in the one-way random effects model with heterogeneous error variances, On the choice of a noninformative prior for Bayesian inference of discretized normal observations, An efficient MCEM algorithm for fitting generalized linear mixed models for correlated binary data, Bayes factors: Prior sensitivity and model generalizability, On the Complexity of Logistic Regression Models, On probability matching priors, On the Bayesianity of minimum risk equivariant estimator for location or scale parameters under a general convex and invariant loss function, Model selection with misspecified spatial covariance structure, Calibrating the prior distribution for a normal model with conjugate prior, A Note on Learning Dependence under Severe Uncertainty, Intrinsic objective Bayesian estimation of the mean of the Tweedie family, Average Most Powerful Tests for a Segmented Regression, Non-informative invariant priors yield peculiar marginals, Dynamic spatial Bayesian models for radioactivity deposition, Bayesian and frequentist prediction limits for the Poisson distribution, Objective Bayesian analysis of spatial data with uncertain nugget and range parameters, Bayesian analysis for a stress-strength system under noninformative priors, Stochastic Collocation Algorithms Using $l_1$-Minimization for Bayesian Solution of Inverse Problems, A note on reference priors for the scalar skew-normal distribution, Adaptive Bayesian prediction of reliability based on degradation process, Quantum sensing networks for the estimation of linear functions, Interval estimation, point estimation, and null hypothesis significance testing calibrated by an estimated posterior probability of the null hypothesis, Discussion: Bayesian Methods: Applied? Yes. Philosophical Defense? In Flux