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 ...

Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in ...

The goal of this talk is to familiarize those in attendance with some common multivariate methods, such as principal component analysis, factor analysis, Hotelling’s T 2, etc. We’ll try to motivate ...

In multivariate recurrent event data regression, observation of recurrent events is usually terminated by other events that are associated with the recurrent event processes, resulting in informative ...

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

Long-term monitoring programs emphasize power analysis as a tool to determine the sampling effort necessary to effectively document ecologically significant changes in ecosystems. Programs that ...