An important problem in principal component analysis (PCA) is the estimation of the correct number of components to retain. PCA is most often used to reduce a set of observed vari...
This paper reports on the development of specific slicing techniques for functional programs and their use for the identification of possible coherent components from monolithic c...
A complex trait like crop yield is determined by its component traits. Multivariable conditional analysis in a general mixed linear model is helpful in dissecting the gene express...
Jixiang Wu, Dongfeng Wu, Johnie N. Jenkins Jr., Ja...
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
: This paper shows an application of two visualization algorithms of multivariate data, U-matrix and Component Planes, in a matter of exploratory analysis of geospatial data. These...