Penalized Maximum Likelihood Method to a Class of Skewness Data Analysis

Xuedong Chen, Qianying Zeng and Qiankun Song

Mathematical Problems in Engineering, 2014, vol. 2014, 1-7

Abstract:

An extension of some standard likelihood and variable selection criteria based on procedures of linear regression models under the skew-normal distribution or the skew- distribution is developed. This novel class of models provides a useful generalization of symmetrical linear regression models, since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions. A generalized expectation-maximization algorithm is developed for computing the penalized estimator. Efficacy of the proposed methodology and algorithm is demonstrated by simulated data.

Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2014/824816.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2014/824816.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:824816

DOI: 10.1155/2014/824816

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().