Classification of Chenopodium Genus Populations and Species Based on Continuous and Categorical Variables

Abstract

The estimation of statistical distance between populations arises in many multivariate analysis techniques. Whereas distance measures for continuous data are well developed, those for mixed discrete and continuous data are less so because of the lack of a standard model for such data. Such mixture of variables arise frequently in the field of medicine, biometry, psychology, econometrics and only comparatively few models have been developed for evaluating distance between populations. The subject of our study were data in the field of botany. The aim of the presented investigation was to apply methods for analysis of dissimilarity between 44 populations of 13 species of Ghenopodium genus,presented by 15 variables - 10 continuous and 5 categorical. The previously developed by another authors distance measures between populations presented by mixed attributes turned out not appropriate for the available data of Chenopodium genus. F or that reason a specific distance measures were applied. The matrices with distances between populations and species were used as input for Hierarchical Cluster Analysis to explore the taxonomic structure of the Chenopodium genus.