View source: R/truncated_distributions.R
| rgammat | R Documentation |
Generate random claim severities from a gamma distribution conditional on
the result falling inside the interval (lower, upper).
rgammat(n, shape, scale, lower, upper)
n |
Integer. Number of observations to generate. |
shape |
Numeric. Shape parameter of the gamma distribution. |
scale |
Numeric. Scale parameter of the gamma distribution. |
lower |
Numeric. Lower truncation bound. |
upper |
Numeric. Upper truncation bound. |
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.
A numeric vector of length n containing random draws from the
truncated gamma distribution.
Martin Haringa
fit_truncated_severity(), rlnormt()
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