nlmixr2auto (version 1.0.0)

get.mod.lst: Summarize parameter estimates and run information from an nlmixr2 fit

Description

Extracts fixed effects, between-subject variability, residual variability, estimation precision, confidence intervals, covariance structure, shrinkage, and key runtime metrics from a fitted model produced by nlmixr2.

Usage

get.mod.lst(fit.s, modi)

Value

A data.frame with parameter summaries, model fit criteria (AIC, BIC, objective function value, log-likelihood, number of estimated parameters) and computation timings extracted from the fitted object.

Arguments

fit.s

A model object generated using nlmixr2.

modi

A numeric identifier used to label the model results, for example when multiple models are evaluated in sequence.

Author

Zhonghui Huang

Details

The function checks for the presence of each element before extraction to ensure robust handling of incomplete estimation or missing covariance results.

Examples

# \donttest{
pheno <- function() {
  ini({
    tcl <- log(0.008) # typical value of clearance
    tv <-  log(0.6)   # typical value of volume
    eta.cl + eta.v ~ c(1,
                       0.01, 1) ## cov(eta.cl, eta.v), var(eta.v)
    add.err <- 0.1    # residual variability
  })
  model({
    cl <- exp(tcl + eta.cl) # individual value of clearance
    v <- exp(tv + eta.v)    # individual value of volume
    ke <- cl / v            # elimination rate constant
    d/dt(A1) = - ke * A1    # model differential equation
    cp = A1 / v             # concentration in plasma
    cp ~ add(add.err)       # define error model
  })
}

# Fit the model using nlmixr2
fit <- nlmixr2est::nlmixr2(pheno, pheno_sd, est="saem", nlmixr2est::saemControl(print=0))

# Extract model results
model_results <- get.mod.lst(fit,1)
print(model_results)
# }