TY - JOUR
T1 - On kernel method for sliced average variance estimation
AU - Zhu, Li-Ping
AU - Zhu, Li-Xing
N1 - Funding Information:
The research described here was supported by a Grant (HKBU 7058/05P) from the Research Grants Council of Hong Kong, and a Grant (FRG/05-06/II-02) from Hong Kong Baptist University, Hong Kong, China. ∗Corresponding author. Hong Kong Baptist University, Hong Kong, China. E-mail address: [email protected] (L.-X. Zhu).
PY - 2007/5
Y1 - 2007/5
N2 - In this paper, we use the kernel method to estimate sliced average variance estimation (SAVE) and prove that this estimator is both asymptotically normal and root n consistent. We use this kernel estimator to provide more insight about the differences between slicing estimation and other sophisticated local smoothing methods. Finally, we suggest a Bayes information criterion (BIC) to estimate the dimensionality of SAVE. Examples and real data are presented for illustrating our method.
AB - In this paper, we use the kernel method to estimate sliced average variance estimation (SAVE) and prove that this estimator is both asymptotically normal and root n consistent. We use this kernel estimator to provide more insight about the differences between slicing estimation and other sophisticated local smoothing methods. Finally, we suggest a Bayes information criterion (BIC) to estimate the dimensionality of SAVE. Examples and real data are presented for illustrating our method.
KW - Asymptotic normality
KW - Bandwidth selection
KW - Dimension reduction
KW - Kernel estimation
KW - Sliced average variance estimation
KW - Sliced inverse regression
KW - Slicing estimation
UR - http://www.scopus.com/inward/record.url?scp=33947148667&partnerID=8YFLogxK
U2 - 10.1016/j.jmva.2006.11.005
DO - 10.1016/j.jmva.2006.11.005
M3 - Journal article
AN - SCOPUS:33947148667
SN - 0047-259X
VL - 98
SP - 970
EP - 991
JO - Journal of Multivariate Analysis
JF - Journal of Multivariate Analysis
IS - 5
ER -