Inverse regression for ridge recovery II: Numerics

Autor:	Glaws, Andrew, Constantine, Paul G., Cook, R. Dennis
Rok vydání:	2018
Předmět:	Mathematics - Numerical Analysis
Druh dokumentu:	Working Paper
Popis:	We investigate the application of sufficient dimension reduction (SDR) to a noiseless data set derived from a deterministic function of several variables. In this context, SDR provides a framework for ridge recovery. In this second part, we explore the numerical subtleties associated with using two inverse regression methods---sliced inverse regression (SIR) and sliced average variance estimation (SAVE)---for ridge recovery. This includes a detailed numerical analysis of the eigenvalues of the resulting matrices and the subspaces spanned by their columns. After this analysis, we demonstrate the methods on several numerical test problems. Comment: The content has been combined with arXiv:1702.02227
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1802.01541 Zobrazit plný text záznamu View this record from Arxiv