functions to create observed vs fitted and fitted vs scaled pearsons residual plots

Usage

runDiagnostics(model, plotting = "b", save = FALSE, label = NULL)

Arguments

model: Fitted model object (glm or gam)
plotting: Plotting options (default='b'). b: returns both plots, f: returns observed vs fitted only and r: returns scale pearsons residual plot only.
save: (default=FALSE). Logical stating whether plot should be saved into working directory. See label to change directory.
label: Character string indicating an label to be added to the plot when using save = TRUE. Can also include a pathway to a directory of choice.

Value

Two plots:

Observed vs Fitted: Plot of observed vs fitted with concordence correlation and marginal R-squared printed in the plot title.
Fitted vs scaled Pearsons residuals: The red line is a locally weighted least squares regression line of all of the residuals.

Examples

# load data
data(ns.data.re)

model<-glm(birds ~ observationhour + as.factor(floodebb) + as.factor(impact), 
           family='quasipoisson', data=ns.data.re)

runDiagnostics(model)
#> Error in ggplot(df): could not find function "ggplot"