Operational Multivariate Analyses by Successive Corrections

Multivariate Models for Operational Risk

In Böcker and Klüppelberg (2005) we presented a simple approximation of OpVaR of a single operational risk cell. The present paper derives approximations of similar quality and simplicity for the multivariate problem. Our approach is based on modelling of the dependence structure of different cells via the new concept of a Lévy copula. JEL Classifications: G18,G39.

Eigenimages and multivariate analyses

Multivariate analyses in microbial ecology

Environmental microbiology is undergoing a dramatic revolution due to the increasing accumulation of biological information and contextual environmental parameters. This will not only enable a better identification of diversity patterns, but will also shed more light on the associated environmental conditions, spatial locations, and seasonal fluctuations, which could explain such patterns. Comp...

Multivariate Statistical Analyses and Applications

I. Introduction: Multivariate Statistical Analyses comprise a number of statistical methods/tools that may be applied to several fields of empirical investigations. Most of these methods have three characteristics in common: (i) they presume availability of data set, say Z(nxk) (in n observations and k variables; k ≥ 2, n>k), collected from the field (observationally or experimentally); (ii) th...

Evaluation of the Effect of Morphological Traits on Grain Yield in Introduced Faba Bean (Vicia faba L.) by Multivariate Analyses

Determining the relationships between morphological traits is very important in plant breeding. For this purpose, path analysis and biplot analysis are among the most effective statistical methods. To study the morphological traits affecting faba bean seed yield, 12 introduced faba bean genotypes were studied under the influence of 3 concentrations of gibberellic acid based on split plot in a r...