CRAN/E | nlsr

nlsr

Functions for Nonlinear Least Squares Solutions - Updated 2022

Installation

About

Provides tools for working with nonlinear least squares problems. For the estimation of models reliable and robust tools than nls(), where the the Gauss-Newton method frequently stops with 'singular gradient' messages. This is accomplished by using, where possible, analytic derivatives to compute the matrix of derivatives and a stabilization of the solution of the estimation equations. Tools for approximate or externally supplied derivative matrices are included. Bounds and masks on parameters are handled properly.

Key Metrics

Version 2023.8.31
R ≥ 3.5
Published 2023-09-05 233 days ago
Needs compilation? no
License GPL-2
CRAN checks nlsr results

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Maintainer

Maintainer

John C Nash

nashjc@uottawa.ca

Authors

John C Nash

aut / cre

Duncan Murdoch

aut

Fernando Miguez

ctb

Arkajyoti Bhattacharjee

ctb

Material

README
NEWS
Reference manual
Package source

In Views

Optimization

Vignettes

Specifying Fixed Parameters
nlsr Introduction
Symbolic and analytical derivatives in R
nlsr Derivatives
nlsr Background, Development, Examples and Discussion

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

nlsr archive

Depends

R ≥ 3.5

Imports

digest

Suggests

minpack.lm
optimx
numDeriv
knitr
rmarkdown
markdown
Ryacas
Deriv
microbenchmark
MASS
ggplot2
nlraa

Reverse Depends

colf

Reverse Imports

beezdemand
genSEIR
usl