augment.beezdemand_hurdle: Augment a beezdemand_hurdle Model with Fitted Values and...

In beezdemand: Behavioral Economic Easy Demand

Augment a beezdemand_hurdle Model with Fitted Values and Residuals

Description

Returns the original data with fitted values, residuals, and predictions from a hurdle demand model. This enables easy model diagnostics and visualization with the tidyverse.

Usage

## S3 method for class 'beezdemand_hurdle'
augment(x, newdata = NULL, ...)

Arguments

x	An object of class beezdemand_hurdle.
newdata	Optional data frame of new data for prediction. If NULL, uses the original data from the model.
...	Additional arguments (currently unused).

Details

For two-part hurdle models:

• .fitted gives predicted demand on the natural consumption scale

• .fitted_prob gives the predicted probability of positive consumption

• .resid is defined only for positive observations as log(y) - .fitted_link

• Observations with zero consumption have .resid = NA since they are explained by Part I (the zero-probability component), not Part II

Value

A tibble containing the original data plus:

.fitted

Fitted demand values (natural scale)

.fitted_link

Fitted values on log scale (Part II mean)

.fitted_prob

Predicted probability of consumption (1 - P(zero))

.resid

Residuals on log scale for positive observations, NA for zeros

.resid_response

Residuals on response scale (y - .fitted)

Examples

data(apt)
fit <- fit_demand_hurdle(apt, y_var = "y", x_var = "x", id_var = "id")
augmented <- augment(fit)

# Plot residuals
library(ggplot2)
ggplot(augmented, aes(x = .fitted, y = .resid)) +
  geom_point(alpha = 0.5) +
  geom_hline(yintercept = 0, linetype = "dashed")

beezdemand documentation built on March 3, 2026, 9:07 a.m.