Calculates group-level (population) Omax and Pmax from a fitted hurdle demand model.
Examples
# \donttest{
data(apt)
fit <- fit_demand_hurdle(apt, y_var = "y", x_var = "x", id_var = "id")
#> Sample size may be too small for reliable estimation.
#> Subjects: 10, Parameters: 12, Recommended minimum: 60 subjects.
#> Consider using more subjects or the simpler 2-RE model.
#> Fitting HurdleDemand3RE model...
#> Part II: zhao_exponential
#> Subjects: 10, Observations: 160
#> Fixed parameters: 12, Random effects per subject: 3
#> Optimizing...
#> Converged in 81 iterations
#> Computing standard errors...
#> Done. Log-likelihood: 32.81
calc_group_metrics(fit)
#> $Pmax
#> [1] 11.04851
#>
#> $Omax
#> [1] 23.82811
#>
#> $Qmax
#> log_q0
#> 2.156681
#>
#> $method
#> [1] "analytic_lambert_w_hurdle"
#>
#> $is_boundary
#> [1] FALSE
#>
#> $elasticity_at_pmax
#> [1] -1
#>
#> $unit_elasticity_pass
#> [1] TRUE
#>
#> $note
#> NULL
#>
# }
