ParetoPickandsDistribution
ParetoPickandsDistribution[μ,σ,ξ]
gives a Pareto–Pickands distribution with location parameter μ, scale parameter σ and shape parameter ξ.
gives the standard Pareto–Pickands distribution with zero location and unit scale parameters.
Details
- The ParetoPickandsDistribution is also known as generalized Pareto distribution or GPD.
- ParetoPickandsDistribution allows σ to be any positive real number and μ and ξ to be any real numbers.
- The probability density function for value in the generalized Pareto distribution is proportional to for and , and for for and . »
- The survival function for value in the generalized Pareto distribution equals for and , and for for and .
- The hazard function for value in the generalized Pareto distribution equals for and , and zero otherwise. »
- ParetoPickandsDistribution can be used with such functions as Mean, CDF and RandomVariate.
Examples
open allclose allBasic Examples (4)
Scope (7)
Generate a sample of pseudorandom numbers from generalized Pareto distribution:
Compare data histogram to the population PDF:
Generate a sample of pseudorandom numbers from generalized Pareto distribution:
Estimate the distribution parameters from sample data:
Compare sample histogram with probability density functions of the estimated distribution:
Skewness of the generalized Pareto distribution depends only on ξ where defined:
Invert skewness as a function of the shape parameter ξ:
Visualize the inverse function:
Kurtosis of Pareto–Pickands distribution only depends on the shape parameter where defined:
The minimal value of the kurtosis within the family of Pareto–Pickands distributions:
Table of moments of Pareto–Pickands distribution:
Closed form for symbolic order:
Closed form for symbolic order:
Quantile function of Pareto–Pickands distribution:
Consistent use of Quantity in parameters yields QuantityDistribution:
Applications (2)
Model a tail of a power‐tail distribution, e.g. StudentTDistribution:
Truncate data to the left at :
Fit truncated data to Pareto–Pickands distribution:
Generate a sample from standard Gaussian distribution:
Define a function to extract largest elements of the sample while shifting the largest element to zero:
Exceedance in large data samples is well described by Pareto–Pickands family of distributions:
Illustrate this fact with a sequence of probability plots of exceedance data against Pareto–Pickands family of distributions:
Properties & Relations (8)
Pareto–Pickands distribution family is closed under affine transformations:
Pareto–Pickands distribution family is closed under left truncation (threshold stability):
Refine the result, assuming that truncation point belongs to the support of ParetoPickandsDistribution:
Pareto–Pickands distribution with is equivalent to a UniformDistribution:
Pareto–Pickands distribution with is equivalent to a shifted ExponentialDistribution:
The Pareto–Pickands distribution family includes ParetoDistribution of types I and II:
Check that probability density functions coincide:
Standard Pareto–Pickands distribution with a positive shape parameter ξ is a special case of TsallisQExponentialDistribution:
Standard Pareto–Pickands distributions are stochastically ordered, i.e. for any two parameters , cumulative distributions functions are (reverse) ordered for all :
Pareto–Pickands distribution with positive shape parameter ξ occurs as a parametric mixture of ExponentialDistribution whose rate follows a GammaDistribution:
Text
Wolfram Research (2019), ParetoPickandsDistribution, Wolfram Language function, https://reference.wolfram.com/language/ref/ParetoPickandsDistribution.html.
CMS
Wolfram Language. 2019. "ParetoPickandsDistribution." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/ParetoPickandsDistribution.html.
APA
Wolfram Language. (2019). ParetoPickandsDistribution. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/ParetoPickandsDistribution.html