In this paper we present a widely applicable definition of the predictive likelihood based on estimators that are either sufficient or approximately sufficient. Under regularity conditions, this predictive likelihood is shown to equal the Bayes prediction density up to terms of order O p(n-1)....

Kim, Shephard and Chib (1998) provided a Bayesian analysis of stochastic volatility models based on a fast and reliable Markov chain Monte Carlo (MCMC) algorithm. Their method ruled out the leverage effect, which is known to be important in applications. Despite this, their basic method has been...

In finance and economics, there is a great deal of work on the theoretical modeling and statistical estimation of the yield curve (defined as the relation between $-\frac{1}{\tau }\log p_{t}(\tau )$ and $\tau$, where $p_{t}(\tau )$ is the time $t$ price of the zero-coupon bond with payoff 1 at...

Zellner (1975), Chaloner and Brant (1988), and Chaloner (1991) used the posterior distributions of the realized errors to define outliers in a linear model. The same concept is used here to define outliers in a state-space model. An effective approach to compute the posterior probabilities of...

The method of Bayesian model selection for join point regression models is developed. Given a set of "K"+1 join point models "M"₀, "M"₁, …, "M"_{" K"} with 0, 1, …, "K" join points respec-tively, the posterior distributions of the parameters and competing models "M"_"k" are computed...

A very general measure of skewness based on the quantiles is introduced, which includes several well-known measures as special cases. Sample versions of our measure may be used as test statistics for testing the hypothesis of symmetry about an unknown value. We provide large sample theory for...