We derive analytic expressions for the tail behavior of credit losses in a large homogeneous credit default portfolio. Our model is an extended CreditMetrics model; i.e. it is a one-factor model with a multiplicative shock-variable. We show that the first order tail behavior is robust with respect to this shockvariable. In a simulation study we compare different models for the latent variables....

Searching images from the World Wide Web in order to know what an object looks like is a very common task. The best response for such a task is to present the most typical image of the object. Existing web-based image search engines, however, return many results that are not typical. In this paper, we propose a method for obtaining typical images through estimating parameters of a generative mo...

This article describes a general class of factor analytic models for the analysis of clustered multivariate data in the presence of informative missingness. We assume that there are distinct sets of cluster-level latent variables related to the primary outcomes and to the censoring process, and we account for dependency between these latent variables through a hierarchical model. A linear model...

Our concern is selecting the concentrationmatrix’s nonzero coefficients for a sparse Gaussian graphical model in a high-dimensional setting. This corresponds to estimating the graph of conditional dependencies between the variables.We describe a novel framework taking into account a latent structure on the concentration matrix. This latent structure is used to drive a penalty matrix and thus to...

We apply a new Bayesian data analysis technique (latent process decomposition) to four recent microarray datasets for breast cancer. Compared to hierarchical cluster analysis, for example, this technique has advantages such as objective assessment of the optimal number of sample or gene clusters in the data, penalization of overcomplex models fitting to noise in the data and a common latent spa...

Communication mechanisms are introduced into the program schemes of Concurrent Dynamic Logic, on both the propositional and the first-order levels. The elfects of these mechanisms (particularly, channels, shared variables, and “message collectors”) on issues of expressiveness and decidability are investigated. In general, we find that both respects are dominated by the extent to which the capab...

We consider the problem of parameter estimation using weakly supervised datasets, where a training sample consists of the input and a partially specified annotation, which we refer to as the output. The missing information in the annotation is modeled using latent variables. Traditional methods, such as expectation-maximization, overburden a single distribution with two separate tasks: (i) mode...