Conditional dependence is expressed as a projection map in the trivariate copula space. The projected copula, its sample counterpart and the related process are defined. The weak convergence of the projected copula process to a tight centered Gaussian Process is obtained under weak assumptions...

Consider the probability of random time absolute ruin in the renewal risk model with constant premium rate and constant force of interest. We assume that claim sizes Xi,i=1,2,…, are conditionally independent on some sigma algebra and that the common distribution belongs to class D∩L. We...

A simple and explicit procedure for testing the conditional independence of two multi-dimensional random variables given a third random vector is described. The associated L1-based test statistic is defined for when the empirical distribution of the variables is restricted to finite partitions....

Motivated by Florens et al. (1993) and recent studies of stochastic systems with memory, we suggest the new concept of causality for continuous time stochastic processes which deal with finite horizon of the past. Also, we present results which show connections between the given concept of...

In this paper we consider conditionally independent processes with respect to some dynamic factor. We derive some mixing properties for random processes when conditioning is given with respect to unbounded memory of the factor. Our work is motivated by some real examples related to risk theory.

This paper proposes and studies a tractable subset of Nash equilibria, belief-free review-strategy equilibria, in repeated games with private monitoring. The payoff set of this class of equilibria is characterized in the limit as the discount factor converges to one for games where players...

We empirically investigate the short-run impact of anticipated and unanticipated unemployment rates on stock prices. We particularly examine the nonlinearity in stock market’s reaction to unemployment rate and study the effect at each individual point (quantile) of stock return distribution....

With sparse structures and conditional independence, one could estimate the precision matrix of Gaussian graphical models more efficiently. Sun and Sun (2005) studied objective priors for star-shape graphical models. We consider a generative star-shape model. Objective priors such as invariance...

The aim of this paper is to provide a graphical representation of the dynamic relations among the marginal processes of a first order multivariate Markov chain. We show how to read Granger-noncausal and contemporaneous independence relations off a particular type of mixed graph, when directed...

A variable selection method for constructing decision trees with rank data is proposed. It utilizes conditional independence tests based on loglinear models for contingency tables. Compared with other selection methods, our method is computationally more efficient. Moreover, our method is...