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Pareto  

The Pareto, Piecewise Pareto and Generalized Pareto Distribution
View on CRAN: Click here


Download and install Pareto package within the R console
Install from CRAN:
install.packages("Pareto")

Install from Github:
library("remotes")
install_github("cran/Pareto")

Install by package version:
library("remotes")
install_version("Pareto", "2.4.5")



Attach the package and use:
library("Pareto")
Maintained by
Ulrich Riegel
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-12-17
Latest Update: 2023-04-18
Description:
Utilities for the Pareto, piecewise Pareto and generalized Pareto distribution that are useful for reinsurance pricing. In particular, the package provides a non-trivial algorithm that can be used to match the expected losses of a tower of reinsurance layers with a layer-independent collective risk model. The theoretical background of the matching algorithm and most other methods are described in Ulrich Riegel (2018) .
How to cite:
Ulrich Riegel (2019). Pareto: The Pareto, Piecewise Pareto and Generalized Pareto Distribution. R package version 2.4.5, https://cran.r-project.org/web/packages/Pareto
Previous versions and publish date:
1.1.0 (2019-12-17 16:50), 1.1.3 (2020-02-14 00:10), 1.1.5 (2020-04-03 11:30), 2.0.0 (2020-05-02 09:40), 2.1.0 (2020-07-09 23:50), 2.2.0 (2020-08-03 08:40), 2.2.1 (2020-09-11 15:30), 2.2.2 (2021-01-28 00:00), 2.3.0 (2021-02-07 06:10), 2.4.0 (2021-02-18 10:50), 2.4.2 (2021-03-03 10:30), 2.4.4 (2023-04-08 15:40)
Other packages that cited Pareto R package
View Pareto citation profile
Other R packages that Pareto depends, imports, suggests or enhances
Functions, R codes and Examples using the Pareto R package
Some associated functions: Example1_AP . Example1_EL . Excess_Frequency.PGP_Model . Excess_Frequency.PPP_Model . Excess_Frequency . Fit_PML_Curve . Fit_References . GenPareto_Layer_Mean . GenPareto_Layer_SM . GenPareto_Layer_Var . GenPareto_ML_Estimator_Alpha . Layer_Mean.PGP_Model . Layer_Mean.PPP_Model . Layer_Mean . Layer_Sd.PGP_Model . Layer_Sd.PPP_Model . Layer_Sd . Layer_Var.PGP_Model . Layer_Var.PPP_Model . Layer_Var . Local_Pareto_Alpha . PGP_Model . PPP_Model . PPP_Model_Excess_Frequency . PPP_Model_Exp_Layer_Loss . PPP_Model_Layer_Sd . PPP_Model_Layer_Var . PPP_Model_Simulate . Pareto_CDF . Pareto_Extrapolation . Pareto_Find_Alpha_btw_FQ_Layer . Pareto_Find_Alpha_btw_FQs . Pareto_Find_Alpha_btw_Layers . Pareto_Layer_Mean . Pareto_Layer_SM . Pareto_Layer_Var . Pareto_ML_Estimator_Alpha . Pareto_PDF . PiecewisePareto_CDF . PiecewisePareto_Layer_Mean . PiecewisePareto_Layer_SM . PiecewisePareto_Layer_Var . PiecewisePareto_ML_Estimator_Alpha . PiecewisePareto_Match_Layer_Losses . PiecewisePareto_PDF . Simulate_Losses.PGP_Model . Simulate_Losses.PPP_Model . Simulate_Losses . dGenPareto . dPareto . dPiecewisePareto . is.PGP_Model . is.PPP_Model . is.valid.PGP_Model . is.valid.PPP_Model . pGenPareto . pPareto . pPiecewisePareto . print.PGP_Model . print.PPP_Model . qGenPareto . qPareto . qPiecewisePareto . rGenPareto . rPareto . rPiecewisePareto . 
Some associated R codes: CollectiveModelMethods.R . Documentation.R . FitPP.R . Functions.R . PGPModel.R . PPPModel.R . ValidationFunctions.R . lp_functions.R .  Full Pareto package functions and examples
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