It is well known that Jeffreys' prior is asymptotically least favorable under the entropy risk, i.e. it asymptotically maximizes the mutual information between the sample and the parameter. However, in this paper we show that the prior that minimizes (subject to certain constraints) the mutual...

Let Ω be a space of densities with respect to some "σ"-finite measure "μ" and let <b>Π</b> be a prior distribution having support Ω with respect to some suitable topology. Conditional on "f", let <b>X</b>-super-<b>n</b> = ("X"₁&hairsp;,…, &hairsp;"X"_"n") be an independent and identically distributed sample of size <b>"n"</b>...

A new simulation method, "auxiliary random functions" is introduced. When used within a Gibbs sampler, this method enables a unified treatment of exact, right-censored, left-censored, left-truncated and interval censored data, with and without covariates in survival models. The models and...

type="main" xml:id="sjos12047-abs-0001" <title type="main">Abstract</title>This paper examines the use of Dirichlet process mixtures for curve fitting. An important modelling aspect in this setting is the choice between constant and covariate-dependent weights. By examining the problem of curve fitting from a predictive...