Package index • emaxnls

Build

Build Emax regression models

emax_nls(): Emax model with arbitrary covariates (does not support interactions)

emax_forward() emax_backward(): Stepwise covariate modelling for Emax regression

emax_add_term() emax_remove_term(): Add or remove a covariate term from an Emax regression

Methods

Methods for Emax regression objects

print(<emaxnls>): Print an Emax regression model object

coef(<emaxnls>): Coefficents for an Emax regression

vcov(<emaxnls>): Variance-covariance matrix for an Emax regression

confint(<emaxnls>): Confidence intervals for Emax regression model parameters

residuals(<emaxnls>): Residuals for an Emax regression

logLik(<emaxnls>): Log-likelihood for an Emax regression model

AIC(<emaxnls>) BIC(<emaxnls>): Akaike information criterion / Bayesian information criterion

anova(<emaxnls>): Analysis of variance for Emax regression models

simulate(<emaxnls>): Simulate responses from Emax regression model

predict(<emaxnls>): Predicting from Emax regression models

deviance(<emaxnls>): Model deviance for an Emax regression

df.residual(<emaxnls>): Residual degrees of freedom for an Emax regression model

fitted(<emaxnls>): Fitted values for an Emax regression

nobs(<emaxnls>): Number of observations for an Emax regression model

sigma(<emaxnls>): Residual standard deviation for Emax regression models

Other

Other exported objects

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