Document Type
Article
Language
eng
Format of Original
16 p.
Publication Date
3-2016
Publisher
Elsevier
Source Publication
Journal of Multivariate Analysis
Source ISSN
0047-259X
Abstract
Traditional factor models explicitly or implicitly assume that the factors follow a multivariate normal distribution; that is, only moments up to order two are involved. However, it may happen in real data problems that the first two moments cannot explain the factors. Based on this motivation, here we devise three new skewed factor models, the skew-normal, the skew-t, and the generalized skew-normal factor models depending on a selection mechanism on the factors. The ECME algorithms are adopted to estimate related parameters for statistical inference. Monte Carlo simulations validate our new models and we demonstrate the need for skewed factor models using the classic open/closed book exam scores dataset.
Recommended Citation
Kim, Hyoung-Moon; Maadooliat, Mehdi; Arellano-Valle, Reinaldo B.; and Genton, Marc G., "Skewed Factor Models Using Selection Mechanisms" (2016). Mathematics, Statistics and Computer Science Faculty Research and Publications. 460.
https://epublications.marquette.edu/mscs_fac/460
Comments
Accepted version. Journal of Multivariate Analysis, Vol. 145 (March 2016): 162-177. DOI. © 2016 Elsevier. Used with permission.