[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.5351/CKSS.2012.19.6.793

Hidden Truncation Normal Regression

Kim, Sungsu (Applied Statistics Unit, Indian Statistical Institute)

Publication Information

Communications for Statistical Applications and Methods / v.19, no.6, 2012 , pp. 793-798 More about this Journal

Abstract

In this paper, we propose regression methods based on the likelihood function. We assume Arnold-Beaver Skew Normal(ABSN) errors in a simple linear regression model. It was shown that the novel method performs better with an asymmetric data set compared to the usual regression model with the Gaussian errors. The utility of a novel method is demonstrated through simulation and real data sets.

Keywords

Arnold-Beaver skew normal distribution; asymmetric errors; goodness of fit test; simple linear regression;

Citations & Related Records

Reference

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