Year of Publication
Doctor of Philosophy (PhD)
Arts and Sciences
Dr. Xiangrong Yin
The T-central subspace allows one to perform sufficient dimension reduction for any statistical functional of interest. We propose a general estimator using a third moment kernel to estimate the T-central subspace. In particular, in this dissertation we develop sufficient dimension reduction methods for the central mean subspace via the regression mean function and central subspace via Fourier transform, central quantile subspace via quantile estimator and central expectile subsapce via expectile estima- tor. Theoretical results are established and simulation studies show the advantages of our proposed methods.
Digital Object Identifier (DOI)
This dissertation is supported in part by National Science Foundation grant CIF- 1813330. (01/2019 - 05/2019)
Ren, Weihang, "MOMENT KERNELS FOR T-CENTRAL SUBSPACE" (2020). Theses and Dissertations--Statistics. 48.