predict.cp_model_lmer: Predict from a Mixed-Effects Cross-Price Demand Model

In brentkaplan/beezdemand: Behavioral Economic Easy Demand

Predict from a Mixed-Effects Cross-Price Demand Model

Description

Generates predictions from a mixed-effects cross-price demand model (of class cp_model_lmer). The function supports two modes:

Usage

## S3 method for class 'cp_model_lmer'
predict(object, newdata = NULL, pred_type = c("fixed", "random"), ...)

Arguments

object	A cp_model_lmer object (as returned by fit_cp_linear(type = "mixed", ...)).
newdata	A data frame containing at least an x column. For pred_type = "random", an id column is required. If absent, the function extracts unique ids from object$data and expands the grid accordingly. If no ids are available, a default id of 1 is used (with a warning).
pred_type	Character string specifying the type of prediction: either "fixed" (population-level) or "random" (subject-specific). The default is "fixed".
...	Additional arguments passed to the underlying predict function.

Details

"fixed"

Returns predictions based solely on the fixed-effects component (using re.form = NA).

"random"

Returns subject-specific predictions (fixed plus random effects) (using re.form = NULL).

Value

A data frame containing all columns of newdata plus a column y_pred with the corresponding predictions.

Examples

## Not run: 
# Population-level predictions:
predict(fit_out_3, newdata = ex_sub, pred_type = "fixed")

# Subject-specific predictions:
predict(fit_out_3, newdata = ex_sub, pred_type = "random")

## End(Not run)

brentkaplan/beezdemand documentation built on June 11, 2025, 3:50 a.m.