denoiseR：一个低秩矩阵估计软件包
denoiseR: A Package for Low Rank Matrix Estimation
摘要：
我们介绍denoiseR，一个R包，提供了一个统一的实现几个国家的最先进的建议，正则化低秩矩阵估计，以及自动选择的正则化参数。我们还扩展了这些方法以允许缺失值。本文讨论的正则化方案是围绕奇异值收缩和基于自举的稳定性参数构建的。我们通过将其应用于几个真实和模拟数据集来说明如何使用该包，并突出不同实现方法的优点和缺点。
英文摘要：
We introduce denoiseR, an R package that provides a unified implementation of several state-of-the-art proposals for regularized low rank matrix estimation, along with automatic selection of the regularization parameters. We also extend these methods to allow for missing values. The regularization schemes discussed in this paper are built around singular-value shrinkage and bootstrap-based stability arguments. We illustrate how to use out package by applying it to several real and simulated datasets, and highlight strengths and weaknesses of the different implemented methods.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
