Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/99370
Title: Empirical likelihood confidence intervals for nonparametric functional data analysis
Authors: Lian, Heng
Issue Date: 2012
Source: Lian, H. (2012). Empirical likelihood confidence intervals for nonparametric functional data analysis. Journal of Statistical Planning and Inference, 142(7), 1669-1677.
Series/Report no.: Journal of statistical planning and inference
Abstract: We consider the problem of constructing confidence intervals for nonparametric functional data analysis using empirical likelihood. In this doubly infinite-dimensional context, we demonstrate the Wilk's phenomenon and propose a bias-corrected construction that requires neither undersmoothing nor direct bias estimation. We also extend our results to partially linear regression models involving functional data. Our numerical results demonstrate improved performance of the empirical likelihood methods over normal approximation-based methods.
URI: https://hdl.handle.net/10356/99370
http://hdl.handle.net/10220/17246
ISSN: 0378-3758
DOI: http://dx.doi.org/10.1016/j.jspi.2012.02.008
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SPMS Journal Articles

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