Plot Residual Diagnostics

Creates diagnostic plots for model residuals including residuals vs fitted, scale-location, and histogram of residuals.

Usage

plot_residuals(object, type = c("all", "fitted", "histogram", "qq"), ...)

Arguments

object

A fitted model object.

type

Character; type of residual plot. One of:

• "fitted": Residuals vs fitted values

• "histogram": Histogram of residuals

• "qq": Q-Q plot of residuals

• "all": All plots combined (default)

...

Additional arguments passed to plotting functions.

Value

A ggplot2 object or list of ggplot2 objects.

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_residuals(fit)
#> $fitted
#> `geom_smooth()` using formula = 'y ~ x'

#> 
#> $histogram

#> 
#> $qq

#> 
#> attr(,"class")
#> [1] "beezdemand_diagnostic_plots" "list"                       
# }