Generate random claim severities from a gamma distribution conditional on the result falling inside the interval \((lower, upper)\).
rgammat(n, shape, scale, lower, upper)A numeric vector of length n containing random draws from the
truncated gamma distribution.
Integer. Number of observations to generate.
Numeric. Shape parameter of the gamma distribution.
Numeric. Scale parameter of the gamma distribution.
Numeric. Lower truncation bound.
Numeric. Upper truncation bound.
Martin Haringa
Random values are generated by sampling from a uniform distribution on the interval \([F(lower), F(upper)]\), where \(F\) is the CDF of the gamma distribution, and then applying the inverse CDF.
The resulting sample follows the specified conditional distribution; values outside the truncation interval are not generated.
In severity analysis, this can be used for simulation and model checking when the available claims are observed only between a lower reporting threshold and an upper modelling limit. Truncation should not be confused with censoring or capping: the function assumes that values outside the interval are absent rather than recorded at a boundary.
fit_truncated_severity(), rlnormt()