Return the portfolio diagnostics stored when derive_tariff_segments()
created the candidate segmentation. The summary can be used to assess
whether the proposed intervals contain sufficient exposure and claim
information before they are used in a GLM or tariff structure.
# S3 method for tariff_segments
summary(object, ...)A data frame with one row per candidate segment and the columns:
Candidate tariff interval.
Number of portfolio rows assigned to the interval.
Number of distinct observed risk-factor values represented by the interval.
Total exposure represented in a frequency or risk-premium GAM.
Total observed claim count for a frequency or severity GAM.
Observed claim frequency, calculated as claim_count / exposure, for a frequency GAM.
Total observed claim amount for a severity GAM.
Observed average severity, calculated as
claim_amount / claim_count, for a severity GAM.
Total exposure-weighted risk-premium amount for a risk-premium GAM.
Observed risk premium, calculated as
risk_premium_amount / exposure, for a risk-premium GAM.
The response columns are model dependent. The returned table therefore
contains the numerator, denominator and observed y-axis measure relevant to
the model used by risk_factor_gam().
A "tariff_segments" object returned by
derive_tariff_segments().
Additional arguments reserved for method compatibility.
Martin Haringa
derive_tariff_segments(), add_tariff_segments()