Multivariate analysis lies at the foundations of the study of dependencies among characteristics, time, and space. Hundreds of applications in fields such as genomics, communications, social networks, and images, have spawn a massive amount of information and a new order of complexity to multivariate problems, underscoring their versatility, and promoting new ways of practicing Statistics.

We face new dilemmas and must develop methods to cope with problems in which samples are still small, or not increasing in size at the same rate as the parameter space does with a number of variables disproportionately large; problems in which multiple comparisons inherently pose new perspectives, and where multivariate analysis theory can be refined both through its development, and through the use of the growing availability of computational resources.

In this workshop we will discuss random matrices, large-scale inference problems, and multivariate distribution theory, as central axes.

We invite you to celebrate the International Year of Statistics by participating in this event, which will will bring together skilled experts in this field for two and a half days of intense academic activity. We wish to extend a special invitation to young researchers to showcase their work by enrolling in the poster and contributed sessions.

Organizing Commitee:
Graciela González-Farías, CIMAT (
Narayanaswamy Balakrishnan, Mc Master University (
Víctor Pérez-Abreu, CIMAT (

Workshop Secretary:
Rosy Dávalos, CIMAT (