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...

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...

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...

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,...