函数最小化与R中的非线性最小二乘

IF 4.4 2区数学 Q1 STATISTICS & PROBABILITY

Wiley Interdisciplinary Reviews-Computational Statistics Pub Date : 2022-03-24 DOI:10.1002/wics.1580

J. Nash

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引用次数: 0

摘要

这篇综述将使用R来研究函数最小化和非线性最小二乘，可能是边界约束的。这些工具源于数值优化和数学规划的更一般的背景。强调了R开发人员如何试图让不熟悉优化的用户更容易地应用这些工具。文中提到了方法及其实现的一些局限性，以提供透视图。

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Function minimization and nonlinear least squares in R

This review will look at function minimization and nonlinear least squares, possibly bounds constrained, using R. These tools derive from the more general context of numerical optimization and mathematical programming. How R developers have tried to make the application of such tools easier for users not familiar with optimization is highlighted. Some limitations of methods and their implementations are mentioned to provide perspective.

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来源期刊

Wiley Interdisciplinary Reviews-Computational Statistics STATISTICS & PROBABILITY-

CiteScore

6.20

自引率

0.00%

发文量