Testing for the ratio of binomial proportions (often called the relative risk) is quite common in clinical trials and epidemiology study or more generally in the pharmaceutical setting. Although this is an easy problem when we have large sample sizes, it becomes more challenging when sample...

We define and investigate classes of statistical models for the analysis of associations between variables, some of which are qualitative and some quantitative. In the cases where only one kind of variables is present, the models are well-known models for either contingency tables or covariance...

Over the past few decades correspondence analysis has gained an international reputation as a powerful statistical tool for the graphical analysis of contingency tables. This popularity stems from its development and application in many European countries, especially France, and its use has...

Log-linear modeling is a popular statistical tool for analysing a contingency table. This presentation focuses on an alternative approach to modeling ordinal categorical data. The technique, based on orthogonal polynomials, provides a much simpler method of model fitting than the conventional...

In this paper, I develop and estimate a dynamic model of strategicnetwork formation with heterogeneous agents. The main theoretical resultis the existence of a unique stationary equilibrium, which characterizesthe probability of observing a specific network in the data. As aconsequence, the...

This paper extends the Laplace estimators proposed by Chernozhukov and Hong (2003) to incorporate the statistic that tests the overidentifying restrictions in the GMM. This information was previously ignored during parameter estimation in econometrics with Bayesian methods. The parameters and...

This paper is concerned with simulation-based inference in generalized models of stochastic volatility defined by heavy-tailed Student-t distributions (with unknown degrees of freedom) and exogenous variables in the observation and volatility equations and a jump component in the observation...

This paper is concerned with the Bayesian analysis of stochastic volatility (SV) models with leverage. Specifically, the paper shows how the often used Kim et al. [1998. Stochastic volatility: likelihood inference and comparison with ARCH models. Review of Economic Studies 65, 361–393] method...

GARCH models are commonly used as latent processes in econometrics, financial economics, and macroeconomics. Yet no exact likelihood analysis of these models has been provided so far. In this paper we outline the issues and suggest a Markov chain Monte Carlo algorithm which allows the...

This paper is concerned with the Bayesian estimation and comparison of flexible, high dimensional multivariate time series models with time varying correlations. The model proposed and considered here combines features of the classical factor model with that of the heavy tailed univariate...