Fit_References: Fit a Collective Model to a Wishlist of References

Description Usage Arguments Value Examples

View source: R/Functions.R

Description

The function fits a collective model to a wishlist of references (expected layer losses and excess frequencies). The function allows to specify the family of the severity distribution that is used. Depending on this distribution family the function works slightly differently:

Usage

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Fit_References(
  Covers = NULL,
  Attachment_Points = NULL,
  Expected_Layer_Losses = NULL,
  Thresholds = NULL,
  Frequencies = NULL,
  model_threshold = min(c(Attachment_Points, Thresholds)),
  default_alpha = 2,
  dispersion = 1,
  alpha_max = 100,
  severity_distribution = "PiecewisePareto",
  ignore_inconsistent_references = FALSE
)

Arguments

Covers

Numeric vector. Vector containing the covers of the layers from the wishlist.

Attachment_Points

Numeric vector. Vector containing the attachment points of the layers from the wishlist.

Expected_Layer_Losses

Numeric vector. Vector containing the expected losses of the layers from the wishlist.

Thresholds

Numeric vector. Contains the thresholds from the whishlist for which excess frequencies are given.

Frequencies

Numeric vector. Expected frequencies excess the Thresholds from the wishlist.

model_threshold

Numerical. Lowest threshold of the fitted piecewise Pareto distribution.

default_alpha

Numerical. Default alpha for situations where an alpha has to be selected.

dispersion

Numerical. Dispersion of the claim count distribution in the resulting PPP_Model.

alpha_max

Numerical. Maximum alpha to be used for the matching.

severity_distribution

Character. Implemented distributions: "PiecewisePareto" (default), "Pareto" and "GenPareto".

ignore_inconsistent_references

Logical. If TRUE then inconsistent references are ignored in case of the piecewise Pareto distribution and the other references are used to fit the model

Value

For severity_distribution = "PiecewisePareto" or "Pareto": 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:

For severity_distribution = "GenPareto": A PGP_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:

Examples

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covers <- c(1000, 1000, 1000)
att_points <- c(1000, 2000, 5000)
exp_losses <- c(100, 50, 10)
thresholds <- c(4000, 10000)
fqs <- c(0.04, 0.005)
fit <- Fit_References(covers, att_points, exp_losses, thresholds, fqs)
Layer_Mean(fit, covers, att_points)
Excess_Frequency(fit, thresholds)
fit <- Fit_References(covers, att_points, exp_losses, thresholds, fqs,
                      severity_distribution = "Pareto")
Layer_Mean(fit, covers, att_points)
Excess_Frequency(fit, thresholds)
fit <- Fit_References(covers, att_points, exp_losses,
                      severity_distribution = "GenPareto")
Layer_Mean(fit, covers, att_points)

Pareto documentation built on March 3, 2021, 5:07 p.m.