This is a preview. Log in through your library . Abstract This study develops a multivariate, nonnormal density function that can accurately and separately account for skewness, kurtosis, ...

The analysis of phenotypic change is important for several evolutionary biology disciplines, including phenotypic plasticity, evolutionary developmental biology, morphological evolution, physiological ...

We propose a sieve maximum likelihood estimation procedure for a broad class of semiparametric multivariate distributions. A joint distribution in this class is characterized by a parametric copula ...

Multivariate analysis is commonly used when we have more than one outcome variables for each observation. For instance, a survey of American adults’ physical and mental health might measure each ...

Before we learn how to perform multivariate regression in Excel, it is important to have a refresher on regression as a whole and multivariate regression in particular. One of the hallmarks of human ...

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) ...

Whenever you have a problem with more than two variables to sort out, multivariate analysis can offer you an answer. It's used in a variety of fields that require the examination of statistical data, ...

This course is available on the MPhil/PhD in Environmental Economics, MPhil/PhD in International Relations, MPhil/PhD in International Relations, MPhil/PhD in Social Policy, MPhil/PhD in Social ...

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 ...