Sankhya: The Indian Journal of Statistics

2005, Volume 67, Pt. 3, 476--498

Local Likelihood Sizer Map

By

Runze Li, Pennsylvania State University, University Park, USA
J.S. Marron, University of North Carolina, Chapel Hill, USA

SUMMARY. The SiZer Map, proposed by Chaudhuri and Marron (1999), is a statistical tool for finding which features in noisy data are strong enough to be distinguished from background noise. In this paper, we propose the local likelihood SiZer map. Some simulation examples illustrate that the newly proposed SiZer map is more efficient in distinguishing features than the original one, because of the inferential advantage of the local likelihood approach. Some computational problems are addressed, with the result that the computational cost in constructing the local likelihood SiZer map is close to  that of the original one.

AMS (1991) subject classification. 62G08, 62G10, 62-09.

Key words and phrases. Confidence bands, generalized linear models, local polynomials, local likelihood, quasi-likelihood, significant features, SiZer map.

Full paper (PDF)