Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## -----------------------------------------------------------------------------
library(insurancerating)
library(dplyr)
df <- MTPL2 |>
mutate(across(c(area), as.factor)) |>
mutate(across(c(area), ~ set_reference_level(., exposure)))
mod1 <- glm(
nclaims ~ area,
offset = log(exposure),
family = poisson(),
data = df
)
mod2 <- glm(
nclaims ~ area + premium,
offset = log(exposure),
family = poisson(),
data = df
)
## -----------------------------------------------------------------------------
model_performance(mod1, mod2)
## -----------------------------------------------------------------------------
rating_table(mod1, mod2, model_data = df, exposure = "exposure") |>
autoplot()
## -----------------------------------------------------------------------------
bootstrap_performance(mod1, df, n_resamples = 100, show_progress = FALSE) |>
autoplot()
## -----------------------------------------------------------------------------
check_overdispersion(mod1)
## -----------------------------------------------------------------------------
check_residuals(mod1, n_simulations = 600) |>
autoplot()
## -----------------------------------------------------------------------------
grid <- rating_grid(mod1)
head(grid)
## ----eval = FALSE-------------------------------------------------------------
#
# model_performance(...) # compare fitted models
# rating_table(...) |> autoplot() # inspect coefficient structure
# bootstrap_performance(...) # assess predictive stability
# check_overdispersion(...) # assess dispersion
# check_residuals(...) # inspect residual behaviour
# rating_grid(...) # review model-point structure
#
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