Given the drawbacks of implementing multivariate analysis for mapping multiple traits in genome-wide association study (GWAS), principal component analysis (PCA) has been widely used to generate ...

Let ${\mathrm{Z}}_{{\mathrm{M}}_{1}\times \mathrm{N}}={\mathrm{T}}^{\frac{1}{2}}\mathrm{X}$ where (T½)2 = T is a positive definite matrix and X consists of ...

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 ...

This is a preview. Log in through your library . Abstract We consider a multivariate heavy-tailed stochastic volatility model and analyze the large-sample behavior of its sample covariance matrix. We ...

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 ...

Four poor prognostic factors were identified and a simple prognostic index was devised. Information from this analysis can be used to aid clinical decision-making, help individual patient risk ...

This course is available on the Global MSc in Management, Global MSc in Management (CEMS MIM), Global MSc in Management (MBA Exchange), MSc in Applied Social Data Science, MSc in European and ...