Log-likelihood for an Emax regression model — logLik.emaxlogistic • emaxnls

Evaluates the log-likelihood of a fitted Emax model at the maximum likelihood estimates. The returned object is compatible with AIC(), BIC(), and likelihood ratio tests via anova().

Usage

# S3 method for class 'emaxlogistic'
logLik(object, REML = FALSE, ...)

# S3 method for class 'emaxnls'
logLik(object, REML = FALSE, ...)

Arguments

object: An emaxnls or emaxlogistic object
REML: For emaxnls objects only REML = FALSE is supported. Ignored for emaxlogistic objects.
...: Ignored

Value

An object of class logLik with at least one attribute, "df" (degrees of freedom), giving the number of estimated parameters in the model.

Details

For emaxnls objects, the log-likelihood is computed under the assumption of normally distributed errors, as returned by stats::logLik.nls(). For emaxlogistic objects, it is the binomial log-likelihood evaluated at the fitted probabilities. The logLik object carries df (number of parameters) and nobs attributes.

Examples

mod_c <- emax_nls(
  structural_model = rsp_1 ~ exp_1,
  covariate_model = list(E0 ~ cnt_a, Emax ~ 1, logEC50 ~ 1),
  data = emax_df,
  opts = emax_nls_options(max_time = 10)
)
logLik(mod_c)
#> 'log Lik.' -296.8216 (df=5)

mod_b <- emax_logistic(
  structural_model = rsp_2 ~ exp_1,
  covariate_model = list(E0 ~ cnt_a, Emax ~ 1, logEC50 ~ 1),
  data = emax_df,
  opts = emax_logistic_options(max_time = 10)
)
logLik(mod_b)
#> 'log Lik.' -165.7349 (df=4)