2.3.6.
Frequency Generators
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A frequency generator is typically used in the context of frequency severity models (single and event claims generation). Also frequency generators could be used for modeling causal dependencies.
Base: Apart from an absolute parameterization it is possible to calibrate the frequency based on number of policies. In a first step a random number is generated according to the selected distribution and parameters. This number is then multiplied with the ‘base’ value. If the underwriting information consists of several risk bands the selected base values will be added up.
Distribution: The following ‘distributions’ are included. In general you will select a discrete distribution.
- chi square quadrat
- constant
- discrete empirical,
- discrete empirical cumulative
- inverse Gaussian
- lognormal (mean, standard deviation)
- lognormal (mu, sigma)
- negative binomial
- normal
- pareto
- poisson
- piece wise linear
- piece wise linear empirical
- student
- triangular
- uniform
Parameter labels will be switched in the tree view, if a different distribution is selected.
Background Information on Random Numbers
We use the SSJ Library from the University of Montreal for random number generators. Currently all random number generators are using F2NL607.
