In semiconductor manufacturing, especially in electrical test data, but also in other parameters, there are often sets of parameters that are very highly correlated. Even a change in the correlation ...

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 ...

A set of desert vegetation-environment data consisting of 22 concrete communities in Southern Sind was analyzed with two multivariate methods, viz. canonical correlation analysis (CCA) and principal ...

The past ten years have witnessed the development of handheld and portable tools, which has introduced new valuable analytical capabilities to quality assurance, quality control and manufacturing ...

A new one-sided test for serial correlation in multivariate time series models is proposed. The test is based on a comparison between a multivariate spectral density estimator and the spectral density ...

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

This video takes us from the univariate ACE model to a multivariate ACE model: from ACE to MACE. We begin with a review of the univariate ACE model, and then extend this to two phenotypes as a ...

Summary statistics for full-scale IQ (n=257,828) were obtained from the Social Science Genetic Association Consortium. Genetic correlations between the multivariate GenLang results (blue-green), ...