beezdemand (version 0.2.0)

augment.beezdemand_nlme: Augment a beezdemand_nlme Model with Fitted Values and Residuals

Description

Returns the original data with fitted values and residuals from a nonlinear mixed-effects demand model. This enables easy model diagnostics and visualization with the tidyverse.

Usage

# S3 method for beezdemand_nlme
augment(x, newdata = NULL, ...)

Value

A tibble containing the original data plus:

.fitted

Fitted values on the model scale (may be transformed, e.g., LL4)

.resid

Residuals on the model scale

.fixed

Fitted values from fixed effects only (population-level)

Arguments

x

An object of class beezdemand_nlme.

newdata

Optional data frame of new data for prediction. If NULL, uses the original data from the model.

...

Additional arguments (currently unused).

Details

The fitted values and residuals are on the same scale as the response variable used in the model. For equation_form = "zben", this is the LL4-transformed scale. For equation_form = "simplified" or "exponentiated", this is the natural consumption scale.

To back-transform predictions to the natural scale for "zben" models, use: ll4_inv(augmented$.fitted)

Examples

# \donttest{
data(ko)
fit <- fit_demand_mixed(ko, y_var = "y_ll4", x_var = "x",
                        id_var = "monkey", factors = "dose", equation_form = "zben")
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")
# }