JSM 2005 - Toronto

Abstract #304188

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 448
Type: Contributed
Date/Time: Wednesday, August 10, 2005 : 2:00 PM to 3:50 PM
Sponsor: General Methodology
Abstract - #304188
Title: Nonconcave Penalized Likelihood with a Diverging Number
Author(s): Heng Peng*+
Companies: Princeton University
Address: Dept of ORFE, Princeton, NJ, 08544, United States
Keywords: Model selection ; nonconcave penalized likelihood ; diverging parameters ; oracle property ; asymptotic normality ; likelihood ratio statistic
Abstract:

Nonconcave penalized likelihood is proposed by Fan and Li (2001) to simultaneously estimate parameters and select important variables. In most model selection problems, the number of parameters should be large and grow with the sample size. In this paper, asymptotic properties of the nonconcave penalized likelihood are established for situations in which the number of parameters tends to infinity as the sample size increases. The asymptotic results are augmented by a simulation study and the newly developed methodology is illustrated by an analysis of a court case on the sexual discrimination of salary.

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