Add to ORKG1.1 Regular von-Mises / uncoupled model We show that a product of von-Mises distributions is a conjugate prior for the ϕ parameter of a toroidal parameterization of the Gaussian distribution. p(ϕ|x,y) ∝ p(y|x, ϕ)p(ϕ) ∝ ex
We review the Bayesian theory of semiparametric inference following Bickel and Kleijn (2012) [5] and...
In Bayesian probability theory, if the posterior distributions p(θ|x) are in the same family as the ...
The current paper introduces new prior distributions on the univariate normal model, with the aim of...
AbstractThis paper discusses characteristics of standard conjugate priors and their induced posterio...
Abstract. There are several ways to parameterize a distribution belonging to an exponential family, ...
Generalised natural conjugate prior densities: Singular multivariate linear model Jose ́ A. Dı́az-Ga...
AbstractThe conjugate prior for the exponential family, referred to also as the natural conjugate pr...
This paper discusses characteristics of standard conjugate priors and their induced posteriors in B...
Given an exponential family of sampling distributions of order k, one may construct in a natural way...
We point out an error in the proof of the main result of the paper of Tanabe et al. (Comput Stat 22...
Let y = θ + e where θ and e are independent random variables so that the regression of y on θ is lin...
We derive rates of contraction of posterior distributions on nonparametric or semiparametric models ...
The family of proper conjugate priors is characterized in a general exponential model for stochastic...
Consider a natural exponential family parameterized by θ. It is well known that the standard conjuga...
Reconsidering generalizations of the original Bayesian framework that have been suggested during the...
We review the Bayesian theory of semiparametric inference following Bickel and Kleijn (2012) [5] and...
In Bayesian probability theory, if the posterior distributions p(θ|x) are in the same family as the ...
The current paper introduces new prior distributions on the univariate normal model, with the aim of...
AbstractThis paper discusses characteristics of standard conjugate priors and their induced posterio...
Abstract. There are several ways to parameterize a distribution belonging to an exponential family, ...
Generalised natural conjugate prior densities: Singular multivariate linear model Jose ́ A. Dı́az-Ga...
AbstractThe conjugate prior for the exponential family, referred to also as the natural conjugate pr...
This paper discusses characteristics of standard conjugate priors and their induced posteriors in B...
Given an exponential family of sampling distributions of order k, one may construct in a natural way...
We point out an error in the proof of the main result of the paper of Tanabe et al. (Comput Stat 22...
Let y = θ + e where θ and e are independent random variables so that the regression of y on θ is lin...
We derive rates of contraction of posterior distributions on nonparametric or semiparametric models ...
The family of proper conjugate priors is characterized in a general exponential model for stochastic...
Consider a natural exponential family parameterized by θ. It is well known that the standard conjuga...
Reconsidering generalizations of the original Bayesian framework that have been suggested during the...
We review the Bayesian theory of semiparametric inference following Bickel and Kleijn (2012) [5] and...
In Bayesian probability theory, if the posterior distributions p(θ|x) are in the same family as the ...
The current paper introduces new prior distributions on the univariate normal model, with the aim of...