TRES: An R Package for Tensor Regression and Envelope Algorithms

IF 5.4 2区 计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Jing Zeng, Wenjing Wang, Xin Zhang
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引用次数: 2

Abstract

Recently, there has been a growing interest in tensor data analysis, where tensor regression is the cornerstone of statistical modeling for tensor data. This package provides the standard least squares estimators and the more efficient envelope estimators for the tensor response regression (TRR) and the tensor predictor regression (TPR) models. Envelope methodology is a relatively new class of dimension reduction techniques that jointly models the regression mean and covariance parameters. Three types of widely applicable envelope estimation algorithms are implemented and applied to both TRR and TPR models.
一个用于张量回归和包络算法的R包
最近,人们对张量数据分析越来越感兴趣,其中张量回归是张量数据统计建模的基石。该软件包为张量响应回归(TRR)和张量预测回归(TPR)模型提供了标准最小二乘估计器和更有效的包络估计器。包络方法是一类比较新的降维技术,它联合建模回归均值和协方差参数。实现了三种广泛应用的包络估计算法,并将其应用于TRR和TPR模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Statistical Software
Journal of Statistical Software 工程技术-计算机:跨学科应用
CiteScore
10.70
自引率
1.70%
发文量
40
审稿时长
6-12 weeks
期刊介绍: The Journal of Statistical Software (JSS) publishes open-source software and corresponding reproducible articles discussing all aspects of the design, implementation, documentation, application, evaluation, comparison, maintainance and distribution of software dedicated to improvement of state-of-the-art in statistical computing in all areas of empirical research. Open-source code and articles are jointly reviewed and published in this journal and should be accessible to a broad community of practitioners, teachers, and researchers in the field of statistics.
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