Algebraic Statistics is an emerging discipline that combines generality and long tradition of algebra with statistical techniques, increasing their ability to solve problems in a diverse spectrum of applications such as the Biostatistics and Biology computer, Industrial Statistics, network reliability, etc ...
The term Statistics Algebra was coined by Pistone, Riccomagno and Wynn in 2001, in a context of applicability of computational algebraic techniques to Statistics. And the aim of Statistics Algebrawith is adapting originally characteristic of other areas for use techniques for solving problems of Statistics and its application to real situations.
The study of genetic information transfer requires from the categorical data tool, among others. This transfer, however, may be studied at many different levels, from the level of the proteins that constitute the genes to the study of hereditary traits. Depending on the level at which we place ourselves and the general laws that regulate them, very different processes and genetic systems can be considered. But regardless of the peculiarities from each process, all of them can be understood as dynamic systems with the particularity that sometimes the interest of the problem is not to study its future evolution, but what happened in the recent, or not so recent, past time.
From the dynamic or evolutionary point of view the study of such objects, even if they could be addressed using proper algebraic or multilinear techniques, provides better results when these techniques are combined with others of statistical nature. Thus, new tools appear for the study and description of the evolutionary process.