Download Multivariate Statistical Analysis in the Real and Complex Domains

Today, ELC would love to share an eBook entitled Multivariate Statistical Analysis in the Real and Complex Domains written by Arak M. Mathai, Serge B. Provost, & Hans J. Haubold and published by Springer.

Multivariate statistical analysis occasionally proves to be a difficult subject for students. The problem arises in part from the reliance on several types of symbols namely subscripts, superscripts, bars, tildes, bold-face characters, lower- and uppercase Roman and Greek letters, etc. However, resorting to such notations is necessary in order to refer to the various quantities involved such as scalars and matrices either in the real or complex domain. The first author was seeking means of making the study of multivariate analysis more accessible and enjoyable.

There are several Special Features that I’d like to point out from the book:

1. Its most distinctive feature is its development of a parallel theory of multivariate analysis in the complex domain side by side with the corresponding treatment of the real cases.

2. In order to avoid resorting to an excessive number of symbols to denote scalar, vector, and matrix variables : All real scalar variables, whether mathematical or random, are denoted by lowercase letters and all real vector/matrix variables are denoted by capital letters, a tilde being placed on the corresponding variables in the complex domain.

3. Matrix methods are utilized throughout the book so as to limit the number of summations, subscripts, superscripts, and so on.

4. The simplified and consistent notation of dX is used to denote the wedge product of the differentials of all functionally independent real scalar variables in X, whether X is a scalar, a vector, or a square or rectangular matrix, with dX˜ being utilized for the corresponding wedge product of differentials in the complex domain.

Download Multivariate Statistical Analysis in the Real and Complex Domains Here