Fit_PML_Curve | R Documentation |
Fits a PPP_Model that matches the values of a PML curve
Fit_PML_Curve(
return_periods,
amounts,
tail_alpha = 2,
truncation = NULL,
truncation_type = "lp",
dispersion = 1
)
return_periods |
Numeric vector. Vector containing the return periods of the PML curve. |
amounts |
Numeric vector. Vector containing the loss amounts corresponding to the return periods. |
tail_alpha |
Numerical. Pareto alpha that is used above the highest amount of the PML curve. |
truncation |
Numeric. If |
truncation_type |
Character. If |
dispersion |
Numerical. Dispersion of the claim count distribution in the resulting PPP_Model. |
A PPP_Model object that contains the information about a collective model with a Panjer distributed claim count and a Piecewise Pareto distributed severity. The object contains the following elements:
FQ
Numerical. Frequency in excess of the lowest threshold of the piecewise Pareto distribution
t
Numeric vector. Vector containing the thresholds for the piecewise Pareto distribution
alpha
Numeric vector. Vector containing the Pareto alphas of the piecewise Pareto distribution
truncation
Numerical. If truncation
is not NULL
and truncation > max(t)
, then the distribution is truncated at truncation
.
truncation_type
Character. If truncation_type = "wd"
then the whole distribution is truncated. If truncation_type = "lp"
then a truncated Pareto is used for the last piece.
dispersion
Numerical. Dispersion of the Panjer distribution (i.e. variance to mean ratio).
Status
Numerical indicator: 0 = success, 1 = some information has been ignored, 2 = no solution found
Comment
Character. Information on whether the fit was successful
return_periods <- c(1, 5, 10, 20, 50, 100)
amounts <- c(1000, 4000, 7000, 10000, 13000, 14000)
fit <- Fit_PML_Curve(return_periods, amounts)
1 / Excess_Frequency(fit, amounts)
fit <- Fit_PML_Curve(return_periods, amounts, tail_alpha = 1.5,
truncation = 20000, truncation_type = "wd")
1 / Excess_Frequency(fit, amounts)
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