Results 11 to 20 of about 2,165 (200)
Constrained noninformative priors [PDF]
, 1994 The Jeffreys noninformative prior distribution for a single unknown parameter is the distribution corresponding to a uniform distribution in the transformed model where the unknown parameter is approximately a location parameter.
Atwood, C. L.
core +3 more sources
Reflecting about Selecting Noninformative Priors [PDF]
Journal of Applied & Computational Mathematics, 2016 Following the critical review of Seaman III et al (2012), we re ect onwhat is presumably the most essential aspect of Bayesian statistics, namely theselection of a prior density.
Kamary, Kaniav, Robert, Christian
core +4 more sources
Noninformative Priors for Multivariate Linear Calibration
Journal of Multivariate Analysis, 2000 This paper derives a class of first order probability matching priors and a complete catalog of the reference priors for the general multivariate linear calibration problem.
Yin, Ming
core +2 more sources
Noninformative priors for the two sample normal problem
Test, 1996 Noninformative, Two Sample, Jeffreys Priors, Reference Priors, Probability Matching, Marginalization Paradox,
M. Ghosh, M-Ch. Yang
core +2 more sources
Default Priors in a Zero-Inflated Poisson Distribution: Intrinsic Versus Integral Priors
MathematicsPrior elicitation is an important issue in both subjective and objective Bayesian frameworks, where prior distributions impose certain information on parameters before data are observed.
Junhyeok Hong, Kipum Kim, Seong W. Kim
doaj +2 more sources
Noninformative priors for the normal variance ratio
Statistical Papers, 2007 Frequentist coverage probability, Probability matching priors, Ratio of variances, Reference priors,
D. Kim, S. Kang, W. Lee
core +3 more sources
The Choice of Noninformative Priors for Thompson Sampling in Multiparameter Bandit Models
Proceedings of the AAAI Conference on Artificial IntelligenceThompson sampling (TS) has been known for its outstanding empirical performance supported by theoretical guarantees across various reward models in the classical stochastic multi-armed bandit problems.
Chiang, Chao-Kai +2 more
core +3 more sources
Bayesian analysis of ARMA models using noninformative priors [PDF]
, 1995 Parameters in ARMA models are only locally identified. It is shown that the use of diffuse priors in these models leads to a preference for locally nonidentified parameter values.
Hoek, H., Kleibergen, F.R.
core +6 more sources
Interpretable Variational Graph Autoencoder with Noninformative Prior [PDF]
Future Internet, 2021 Variational graph autoencoder, which can encode structural information and attribute information in the graph into low-dimensional representations, has become a powerful method for studying graph-structured data. However, most existing methods based on variational (graph) autoencoder assume that the prior of latent variables obeys the standard normal ...
Lili Sun +3 more
openaire +2 more sources
A Noninformative Prior on a Space of Distribution Functions [PDF]
Entropy, 2017 In a given problem, the Bayesian statistical paradigm requires the specification of a prior distribution that quantifies relevant information about the unknowns of main interest external to the data. In cases where little such information is available, the problem under study may possess an invariance under a transformation group that encodes a lack of
Alexander Terenin, David Draper
openaire +3 more sources