The BACC software provides its users with tools for Bayesian Analysis, Computation, and Communications. A new version of the software, described here, implements these tools as extensions to popular mathematical applications such as GAUSS or MATLAB. The user has available, within the...

We propose an alternate parameterization of stationary regular finite-state Markov chains, and a decomposition of the parameter into time reversible and time irreversible parts. We demonstrate some useful properties of the decomposition, and propose an index for a certain type of time...

I introduce the HESSIAN method for semi-Gaussian state space models with univariate states. The vector of states a=(a^1; ... ; a^n) is Gaussian and the observed vector y= (y^1 ; ... ; y^n ) need not be. I describe a close approximation g(a) to the density f(a|y). It is easy and fast to evaluate...

McCausland (2004a) describes a new theory of random consumer demand. Theoretically consistent random demand can be represented by a "regular" "L-utility" function on the consumption set X. The present paper is about Bayesian inference for regular L-utility functions. We express prior and...

This paper presents a new theory of random consumer demand. The primitive is a collection of probability distributions, rather than a binary preference. Various assumptions constrain these distributions, including analogues of common assumptions about preferences such as transitivity,...

I introduce the HESSIAN method for semi-Gaussian state space models with univariate states. The vector of states a=(a^1, ... , a^n) is Gaussian and the observed vector y= (y^1 , ... , y^n ) need not be. I describe a close approximation g(a) to the density f(a|y). It is easy and fast to evaluate...

We complete the development of a testing ground for axioms of discrete stochastic choice. Our contribution here is to develop new posterior simulation methods for Bayesian inference, suitable for a class of prior distributions introduced by McCausland and Marley (2013). These prior distributions...