Package: emaxnls 0.1.1

Danielle Navarro

emaxnls: Nonlinear Least Squares Estimation for Emax Regression Models

Provides estimation and covariate selection tools for Emax regression models using nonlinear least squares methods. Supported optimization algorithms are Gauss-Newton, Levenberg-Marquardt, and the port library for bounded optimization. The package also provides tools to assist in simulation work using Emax regression.

Authors:Danielle Navarro [aut, cre, cph]

emaxnls_0.1.1.tar.gz
emaxnls_0.1.1.tar.gz(r-4.7-any)emaxnls_0.1.1.tar.gz(r-4.6-any)
emaxnls_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
emaxnls/json (API)

# Install 'emaxnls' in R:
install.packages('emaxnls', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/djnavarro/emaxnls/issues

Pkgdown/docs site:https://emaxnls.djnavarro.net

Datasets:
  • emax_df - Sample simulated data for Emax exposure-response models with covariates.

On CRAN:

Conda:

1.70 score 3 scripts 10 exports 13 dependencies

Last updated from:1f6912f0c0. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK116
source / vignettesOK190
linux-release-x86_64OK125
wasm-releaseOK138

Exports:emax_add_termemax_convergedemax_funemax_nlsemax_nls_initemax_nls_optionsemax_remove_termemax_scm_backwardemax_scm_forwardemax_scm_history

Dependencies:cliDerivgluelifecyclemagrittrminpack.lmmvtnormpillarpkgconfigrlangtibbleutf8vctrs

Readme and manuals

Help Manual

Help pageTopics
Akaike information criterion / Bayesian information criterionAIC AIC.emaxnls BIC.emaxnls
Analysis of variance for Emax regression modelsanova.emaxnls
Coefficients for an Emax regressioncoef.emaxnls
Confidence intervals for Emax regression model parametersconfint.emaxnls
Model deviance for an Emax regressiondeviance.emaxnls
Residual degrees of freedom for an Emax regression modeldf.residual.emaxnls
Check Emax regression model for convergence statusemax_converged
Sample simulated data for Emax exposure-response models with covariates.emax_df
Construct Emax prediction function from model objectemax_fun
Estimate parameters for an Emax regression modelemax_nls
Construct an initial guess for the Emax model parametersemax_nls_init
Settings used to estimate Emax modelemax_nls_options
Stepwise covariate modeling for Emax regressionemax_scm emax_scm_backward emax_scm_forward emax_scm_history
Add or remove a covariate term from an Emax regressionemax_add_term emax_remove_term emax_update
Fitted values for an Emax regressionfitted.emaxnls
Log-likelihood for an Emax regression modellogLik.emaxnls
Number of observations for an Emax regression modelnobs.emaxnls
Predicting from Emax regression modelspredict.emaxnls
Print an Emax regression model objectprint.emaxnls
Residuals for an Emax regressionresiduals.emaxnls
Residual standard deviation for Emax regression modelssigma.emaxnls
Simulate responses from Emax regression modelsimulate.emaxnls
Summary of an Emax regression modelsummary.emaxnls
Variance-covariance matrix for an Emax regressionvcov.emaxnls