Plot Random Effects Q-Q

Creates Q-Q plots for random effects to assess normality assumptions.

Usage

plot_qq(object, which = NULL, ...)

# S3 method for class 'beezdemand_hurdle'
plot_qq(object, which = NULL, ...)

# S3 method for class 'beezdemand_nlme'
plot_qq(object, which = NULL, ...)

Arguments

object

A fitted model object with random effects (beezdemand_hurdle or beezdemand_nlme).

which

Character vector; which random effects to plot. Default is all.

...

Additional arguments (ignored).

Value

A ggplot2 object.

Examples

# \donttest{
data(apt)
fit <- fit_demand_hurdle(apt, y_var = "y", x_var = "x", id_var = "id")
#> Sample size may be too small for reliable estimation.
#>   Subjects: 10, Parameters: 12, Recommended minimum: 60 subjects.
#>   Consider using more subjects or the simpler 2-RE model.
#> Fitting HurdleDemand3RE model...
#>   Part II: zhao_exponential
#>   Subjects: 10, Observations: 160
#>   Fixed parameters: 12, Random effects per subject: 3
#>   Optimizing...
#>   Converged in 81 iterations
#>   Computing standard errors...
#> Done. Log-likelihood: 32.81
plot_qq(fit)

# }