Title
On permutation tests for predictor contribution in sufficient dimension reduction.
Abstract
To test predictor contribution in a model-free fashion, marginal coordinate tests based on sliced inverse regression (SIR) and sliced average variance estimation (SAVE) have been studied in Cook (2004), and Shao et al. (2007) respectively. Estimating the null distributions of the test statistics is a critical step for such tests. We propose a novel permutation test approach to facilitate the marginal coordinate tests, which applies to existing tests based on SIR and SAVE, and can be readily extended to a new marginal coordinate test based on directional regression (Li and Wang, 2007).
Year
DOI
Venue
2016
10.1016/j.jmva.2016.02.019
Journal of Multivariate Analysis
Keywords
Field
DocType
62F03,62F05
Econometrics,Regression,Sliced inverse regression,Variance estimation,Permutation,Nonparametric statistics,Statistics,Resampling,Sufficient dimension reduction,Statistical hypothesis testing,Mathematics
Journal
Volume
Issue
ISSN
149
C
0047-259X
Citations 
PageRank 
References 
0
0.34
1
Authors
3
Name
Order
Citations
PageRank
Yuexiao Dong134.67
Chaozheng Yang200.34
Zhou Yu327839.88