Multivariate linear regressions are widely used statistical tools in many applications to model the associations between multiple related responses and a set of predictors. To infer such associations, it is often interest test structure regression coefficients matrix, likelihood ratio (LRT) one most popular approaches practice. Despite its popularity, known that classical $\chi^2$ approximation...

This project attempts to predict the interest spread of a property loan based on the borrower and property related attributes. Each attribute can be regarded as a potential feature. The problem is how to predict the spread accurately based on those features. This report describes our approaches of using linear and segmented linear models as well as other clustering methods. The comparative resu...

this paper describes a study of operational parameters by using the multivariate data analysis and neural networks for a municipal waste incinerator located in majorca (spain). the basis of the study also includes the chemometric techniques: linear multivariate regression to develop a model with certain predictive capabilities; linear principal component analysis, which allow the number of vari...

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