Multiple response questions, also known as a pick any/J format, are frequently encountered in the analysis of survey data. The relationship among the responses is difficult to explore when the number ...

XIAO HAN, GUANGMING PAN, QING YANG, A unified matrix model including both CCA and F matrices in multivariate analysis: The largest eigenvalue and its applications, Bernoulli, Vol. 24, No. 4B (November ...

Multivariate analysis of variance (MANOVA) is an extension of the commonly used analysis of variance (ANOVA) method, allowing statistical comparisons across three or more groups of data and involving ...

The primary goal of this short course is to help researchers with multivariate data better visualize and understand their data using multivariate analysis tools. In this course, we will focus on ...

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 ...

Statistics are often viewed as confusing and complicated, but multivariate data analysis (MVA) methods can be used to amass knowledge simply.

Research methods suitable for the analysis of big datasets containing many variables. The fundamentals of data visualisation, customer segmentation, factor analysis and latent class analysis with ...

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 ...