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This repo to allow access to others to working files in nlsr package by J C Nash as of 2022-9-1.

Attempts to alias wrapnlsr() as nlsr() have not been successful. However, explicit copy of code from wrapnlsr() to nlsr() with name changes gives a sane package. Attempts with

nlsr <- wrapnlsr

gave check errors, mainly w.r.t. the .Rd manual files.

JN

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Version

Install

install.packages('nlsr')

Monthly Downloads

492

Version

2023.8.31

License

GPL-2

Maintainer

John C. Nash

Last Published

September 5th, 2023

Functions in nlsr (2023.8.31)

numericDerivR

numericDerivR: numerically evaluates the gradient of an expression. All in R
summary.nlsr

summary.nlsr
nlsrSS

nlsrSS - solve selfStart nonlinear least squares with nlsr package
nlxb

nlxb: nonlinear least squares modeling by formula
sysDerivs

Internal Environments
resid.nlsr

resid.nlsr
resgr

resgr
pnlslm

pnlslm
predict.nlsr

predict.nlsr
print.nlsr

print.nlsr
wrapnlsr

wrapnlsr
pshort

pshort
nlsDeriv

nlsDeriv Functions to take symbolic derivatives.
pnls

pnls
pctrl

pctrl
nvec

nvec
rawres

rawres
prt

prt
resss

resss
residuals.nlsr

residuals.nlsr
coef.nlsr

coef.nlsr
isZERO

Test for constants
SSlogisJN

Alternative self start for three-parameter logistic function SSlogis
fitted.nlsr

fitted.nlsr
jacentral

jacentral
jafwd

jafwd
jaback

jaback
nlsr.control

nlsr.control
nlsr

nlsr function
jand

jand
nlfb

nlfb: nonlinear least squares modeling by functions
model2rjfun

model2rjfun
newSimplification

newSimplification
nlsr.package

nlsr-package Tools for solving nonlinear least squares problems The package provides some tools related to using the Nash variant of Marquardt's algorithm for nonlinear least squares. Jacobians can usually be developed by automatic or symbolic derivatives.
isCALL

isCALL Test if argument is a particular call
newDeriv

newDeriv
findSubexprs

findSubexprs
dex

dex
nlsSimplify

nlsSimplify