Multivariate analysis in statistics is a set of useful methods for analyzing data when there are more than one variables under consideration. Multivariate analysis techniques may be used for several ...

Multivariate analyses such as principal component analysis were among the first statistical methods employed to extract information from genetic markers. From their early applications to current ...

Vector time series data are widely met in practice. In this paper we propose a multivariate functional-coefficient regression model with heteroscedasticity for modelling such data. A local linear ...

Functional data vectors consisting of samples of multivariate data where each component is a random function are encountered increasingly often but have not yet been comprehensively investigated. We ...

MANOVA is a statistical test that extends the scope of the more commonly used ANOVA, that allows differences between three or more independent groups of explanatory (independent or predictor) ...

This course covers multivariate statistical data analysis and experimental design. Students will learn how to extract information by analyzing various engineering datasets, and how to generate ...

Customer perceptions of your company's brand are complex and difficult to predict because of the variety of factors involved. Multivariate analysis uses statistical tools such as multiple regression ...