## Abstract Principal component analysis (PCA) and factor analysis (FA) are often used to uncover genetic factors that contribute to complex disease phenotypes. The purpose of such an analysis is to distill a genetic signal from a large number of correlated phenotype measurements. That signal can t
Factor Analysis and Principal Components
β Scribed by H. Schneeweiss; H. Mathes
- Publisher
- Elsevier Science
- Year
- 1995
- Tongue
- English
- Weight
- 780 KB
- Volume
- 55
- Category
- Article
- ISSN
- 0047-259X
No coin nor oath required. For personal study only.
β¦ Synopsis
The principal components of a vector of random variables are related to the common factors of a factor analysis model for this vector. Conditions are presented under which components and factors as well as factor proxies come close to each other. A similar analysis is carried out for the matrices of loadings of principal components and factor analysis. (C) 1995 Academic Press. Inc.
π SIMILAR VOLUMES
In this paper we show the usage of robust multivariate statistical methods in geostatistics. A usual procedure to estimate the values of variables (e.g. geochemical variables) measured at certain points of a region is to apply geostatistical methods like Krige estimation (based on the estimation of