Results 101 to 110 of about 2,165 (200)
Posterior propriety of bivariate lomax distribution under objective priors
, 2019 The Lomax or Pareto II, distribution has been quite widely used for reliability modeling and life testing, and applied to the sizes of computer files on servers, and even application in the biological sciences.
Sang Gil Kang (6591701) +2 more
core +1 more source
Normal correlation : an objective Bayesian approach [PDF]
, 2005 In this paper we give a decision-theoretic oriented, objective Bayesian answer to the problems of point estimating and sharp hypothesis testing about the correlation coefficient of a bivariate Normal population. Under this view both problems are deemed
Juárez, Miguel A.
core
Reference priors in non-normal location problems
Bayesian Statistics;Statistical ...
Steel, M.F.J., Fernández, C.
core
A discussion on Bayesian analysis : Selecting Noninformative Priors
, 2016 In this note, following the publication of Seaman III, Seaman Jr and Stamey(2012) we re ect on an aspect of Bayesian statistics, namely the selection of a priordensity on the parameters.
Kamary, Kaniav
core
Eliciting vague but proper maximal entropy priors in Bayesian experiments
Bayesian inference, Expert opinion, Kullback–Leibler distance, Shannon’s entropy, Noninformative priors, Channel coding, Sensitivity study, Weibull, 65K05, 90C35,
Nicolas Bousquet
core +1 more source
Probability matching priors: a review
, 1999 In recent years, extensive work has been done concerning the derivation of noninformative prior distributions assuring approximate frequentist validity of Bayesian inferences.This paper provides a review of matching priors obtained via quantiles and via ...
Scricciolo, Catia
core
Bayes factors for a test about the drift of the Brownian motion under noninformative priors
Brownian motions are useful in modeling many stochastic phenomena. We address the problem of default testing for the sign of the drift, if any, in the mean of the process using the Bayesian approach.
Sivaganesan, S., Lingham, Rama T.
core
Noninformative Bayesian Priors. Interpretation And Problems With Construction And Applications.
, 1998 Introduction Central in Bayesian statistics is Bayes' theorem, which can be written as follows: ß(`jx) / f(xj`)ß(`): Given the likelihood function f(xj`) and the prior ß(`), it is easy to calculate the posterior distribution of `, ß(`jx), which ...
Anne Randi Syversveen
core
Comparing Models of Macroeconomic Fluctuations: How Big Are the Differences?
I generate priors for a VAR from four competing models of economic fluctuations: a standard RBC model, Fisher’s (2006) investment-specific technology shocks model, an RBC model with capital adjustment costs and habit formation, and a sticky price model ...
Ghent, Andra
core
Benchmark priors for Bayesian models averaging [PDF]
In contrast to a posterior analysis given a particular sampling model, posterior model probabilities in the context of model uncertainty are typically rather sensitive to the specification of the prior.
Carmen Fernandez, E Ley, Mark F J Steel
core