itdr: An R package of Integral Transformation Methods to Estimate the SDR Subspaces in Regression

Author name not available (Why is that?)

Publication date: 13 April 2022

Abstract: Sufficient dimension reduction (SDR) is a successful tool in regression models. It is a feasible method to solve and analyze the nonlinear nature of the regression problems. This paper introduces the itdr R package that provides several functions based on integral transformation methods to estimate the SDR subspaces in a comprehensive and user-friendly manner. In particular, the itdr package includes the Fourier method (FM) and the convolution method (CM) of estimating the SDR subspaces such as the central mean subspace (CMS) and the central subspace (CS). In addition, the itdr package facilitates the recovery of the CMS and the CS by using the iterative Hessian transformation (IHT) method and the Fourier transformation approach for inverse dimension reduction method (invFM), respectively. Moreover, the use of the package is illustrated by three datasets. Furthermore, this is the first package that implements integral transformation methods to estimate SDR subspaces. Hence, the itdr package may provide a huge contribution to research in the SDR field.

Has companion code repository: https://github.com/tharindupdealwis/itdr

This page was built for publication: itdr: An R package of Integral Transformation Methods to Estimate the SDR Subspaces in Regression

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6396791)