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 φ and analyze its properties. The enriched standard conjugate family for φ and the mean parameter μ are defined and discussed. This family is considerably more flexible than the standard conjugate one. The reference priors for φ and μ are obtained and shown to belong to the enriched standard conjugate family; in particular, this allows us to verify that reference posteriors are always proper. The above results extend th...
For a normally distributed random matrixYwith a general variance-covariance matrix[Sigma]Y, and for ...
Abstract. Classical Wishart distributions on the open convex cones of posi-tive definite matrices an...
[[abstract]]For a normal random variable Y with mean zero and general covari- ance matrix Y the Wish...
A general Wishart family on a symmetric cone is a natural exponential family (NEF) having a homogene...
Consider a standard conjugate family of prior distributions for a vectorparameter indexing an expone...
AbstractReference analysis is one of the most successful general methods to derive noninformative pr...
Reference analysis is one of the most successful general methods to derive noninformative prior dis...
Reference analysis is one of the most successful general methods to derive noninformative prior dis...
Consider a natural exponential family parameterized by θ. It is well known that the standard conjuga...
In the framework of Gaussian graphical models governed by a graph G, Wishart distributions can be de...
AbstractIn this paper the problem of estimating a covariance matrix parametrized by an irreducible s...
We present a systematic study of Riesz measures and their natural exponential families of Wishart la...
En analyse multivariée de données de grande dimension, les lois de Wishart définies dans le contexte...
Abstract. There are several ways to parameterize a distribution belonging to an exponential family, ...
Bayesian Inference, Conjugate Parameterisation, Enriched Prior, Extended Conjugate Family, Posterior...
For a normally distributed random matrixYwith a general variance-covariance matrix[Sigma]Y, and for ...
Abstract. Classical Wishart distributions on the open convex cones of posi-tive definite matrices an...
[[abstract]]For a normal random variable Y with mean zero and general covari- ance matrix Y the Wish...
A general Wishart family on a symmetric cone is a natural exponential family (NEF) having a homogene...
Consider a standard conjugate family of prior distributions for a vectorparameter indexing an expone...
AbstractReference analysis is one of the most successful general methods to derive noninformative pr...
Reference analysis is one of the most successful general methods to derive noninformative prior dis...
Reference analysis is one of the most successful general methods to derive noninformative prior dis...
Consider a natural exponential family parameterized by θ. It is well known that the standard conjuga...
In the framework of Gaussian graphical models governed by a graph G, Wishart distributions can be de...
AbstractIn this paper the problem of estimating a covariance matrix parametrized by an irreducible s...
We present a systematic study of Riesz measures and their natural exponential families of Wishart la...
En analyse multivariée de données de grande dimension, les lois de Wishart définies dans le contexte...
Abstract. There are several ways to parameterize a distribution belonging to an exponential family, ...
Bayesian Inference, Conjugate Parameterisation, Enriched Prior, Extended Conjugate Family, Posterior...
For a normally distributed random matrixYwith a general variance-covariance matrix[Sigma]Y, and for ...
Abstract. Classical Wishart distributions on the open convex cones of posi-tive definite matrices an...
[[abstract]]For a normal random variable Y with mean zero and general covari- ance matrix Y the Wish...