plot_halfnormal {auditor} R Documentation

Half-Normal plot

Description

The half-normal plot is one of the tools designed to evaluate the goodness of fit of a statistical models. It is a graphical method for comparing two probability distributions by plotting their quantiles against each other. Points on the plot correspond to ordered absolute values of model diagnostic (i.e. standardized residuals) plotted against theoretical order statistics from a half-normal distribution.

Usage

plot_halfnormal(object, ..., quantiles = FALSE, sim = 99)

plotHalfNormal(object, ..., quantiles = FALSE, sim = 99)


Arguments

 object An object of class auditor_model_halfnormal created with model_halfnormal function. ... Other auditor_model_halfnormal objects. quantiles If TRUE values on axis are on quantile scale. sim Number of residuals to simulate.

Value

A ggplot object.

model_halfnormal

score_halfnormal

Examples

dragons <- DALEX::dragons[1:100, ]

# fit a model
model_lm <- lm(life_length ~ ., data = dragons)

lm_audit <- audit(model_lm, data = dragons, y = dragons\$life_length)

# validate a model with auditor
hn_lm <- model_halfnormal(lm_audit)

# plot results
plot_halfnormal(hn_lm)
plot(hn_lm)



[Package auditor version 1.3.3 Index]