Add observed portfolio experience to a rating table — add_observed

Attach the output of factor_analysis() to a rating_table() object so it can be shown in autoplot.rating_table(). This is useful when you want to compare fitted GLM relativities with the observed portfolio pattern for the same rating factor.

The observed metric is scaled before plotting. With scale = "reference" the metric is divided by the observed value of the model reference level. If a clear reference level cannot be found, the metric is scaled to its mean. With scale = "mean", the metric is always scaled to its mean.

Usage

add_observed_experience(
  object,
  experience,
  metric = "risk_premium",
  label = "Observed experience",
  color = NULL,
  scale = c("reference", "mean")
)

Arguments

object: A rating_table object returned by rating_table().
experience: A factor_analysis object returned by factor_analysis().
metric: Character; metric from experience to plot. Common choices are "frequency", "average_severity", "risk_premium", "loss_ratio" and "average_premium", depending on which columns were supplied to factor_analysis().
label: Character; legend label for the observed experience line.
color: Optional line color. If NULL, the internal risk premium color is used.
scale: Character; scaling applied before plotting. One of "reference" or "mean".

Value

A rating_table object with observed portfolio experience attached.

Author

Martin Haringa

Examples

df <- MTPL2
df$area <- as.factor(df$area)

model <- glm(
  nclaims ~ area + offset(log(exposure)),
  family = poisson(),
  data = df
)

observed <- factor_analysis(
  df,
  risk_factors = "area",
  claim_count = "nclaims",
  exposure = "exposure"
)

rating_table(model, model_data = df, exposure = "exposure") |>
  add_observed_experience(observed, metric = "frequency") |>
  autoplot(risk_factors = "area")