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.
翻译:足够维度减少(SDR)是回归模型的一个成功工具,是解决和分析回归问题非线性的非线性的一个可行方法。本文介绍一个idr R 软件包,该软件包根据综合转换方法提供若干功能,以综合和方便用户的方式估计SDR子空间;特别是,itdr 软件包包括Fourier法和Convolution法,用于估计SDR子空间,如中央中位子空间和中央子空间。此外,itdr软件包通过使用迭代赫西亚变换法和反向递减法(invFM),为CMS和CS的恢复提供了便利。此外,3个数据集说明了该软件包的使用情况。此外,这是第一个软件包,采用综合转换方法来估计SDR子空间。因此,Idr软件包可能对SDR领域的研究做出巨大贡献。