A corrected version of KIC for robust model selection in small samples

Author

Seghouane, Abd-Krim

Author_Institution

Canberra Res. Lab., Nat. ICT Australia, Canberra, ACT

fYear

2007

fDate

12-15 Feb. 2007

Firstpage

1

Lastpage

4

Abstract

A small sample version of KIC for the selection of least absolute deviations regression models is proposed. In contrast to KIC, the proposed criterion named KIC_L1, where the notation L₁ stands for absolute deviation, provides an exactly unbiased estimator for the expected Kullback symmetric divergence, assuming that the errors have a double exponential distribution and that the true model is correctly specified or overfitted. Simulation results showing that KIC_L1 performs slightly better than KIC are presented.

Keywords

estimation theory; exponential distribution; regression analysis; signal sampling; Kullback information criterion; Kullback symmetric divergence; double exponential distribution; exactly unbiased estimator; least absolute deviation regression model; robust model selection; small KIC sample version; Australia Council; Computational modeling; Error correction; Exponential distribution; Gaussian distribution; Laboratories; Least squares methods; Parameter estimation; Parametric statistics; Robustness;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on

Conference_Location

Sharjah

Print_ISBN

978-1-4244-0778-1

Electronic_ISBN

978-1-4244-1779-8

Type

conf

DOI

10.1109/ISSPA.2007.4555330

Filename

4555330