Get model summaries from a cross-price model — glance.cp_model

This function extracts model summary statistics from a cross-price demand model into a single-row data frame, following the conventions of the broom package. It returns goodness-of-fit measures and other model information.

Usage

# S3 method for class 'cp_model_nls'
glance(x, ...)

Arguments

x: A model object from fit_cp_nls or fit_cp_linear
...: Additional arguments (unused)

Value

A one-row data frame with model summary statistics:

r.squared: R-squared value indicating model fit
aic: Akaike Information Criterion
bic: Bayesian Information Criterion
equation: The equation type used in the model
method: The method used to fit the model
transform: The transformation applied to the data, if any

Examples

# \donttest{
data(etm)
fit <- fit_cp_nls(etm, equation = "exponentiated")
glance(fit)
#> # A tibble: 1 × 6
#>   r.squared   aic   bic equation      method        transform
#>       <dbl> <dbl> <dbl> <chr>         <chr>         <chr>    
#> 1    0.0348 1744. 1758. exponentiated nls_multstart none     
# }