PowerDistribution

PowerDistribution[k,a]

represents a power distribution with domain parameter k and shape parameter a.

Details

Background & Context

Examples

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Basic Examples  (4)

Probability density function:

Cumulative distribution function:

Mean and variance:

Median:

Scope  (8)

Generate a sample of pseudorandom numbers from a power distribution:

Compare its histogram to the PDF:

Distribution parameters estimation:

Estimate the distribution parameters from sample data:

Compare a density histogram of the sample with the PDF of the estimated distribution:

Skewness depends only on the shape parameter:

Limiting values:

Kurtosis depends only on the shape parameter:

Limiting values:

Kurtosis attains its minimum:

Different moments with closed forms as functions of parameters:

Moment:

Closed form for symbolic order:

CentralMoment:

Closed form for symbolic order:

FactorialMoment:

Cumulant:

Hazard function:

Quantile function:

Consistent use of Quantity in parameters yields QuantityDistribution:

Find the median volume:

Applications  (1)

Suppose the variance of normal distribution follows PowerDistribution defined on the unit interval. Find the resulting distribution:

Generate random variates:

Compare sample histogram to the distribution density:

Properties & Relations  (9)

Power distribution is closed under scaling by a positive factor:

Power distribution is closed under Max:

Relationships to other distributions:

KumaraswamyDistribution simplifies to a special case of power distribution:

Power distribution is a transformation of ExponentialDistribution:

ExponentialDistribution can be obtained from power distribution:

Power distribution is a distribution of an inverse of ParetoDistribution:

UniformDistribution is a transformation of PowerDistribution:

PowerDistribution is a special case of PearsonDistribution:

Neat Examples  (1)

PDFs for different a values with CDF contours:

Introduced in 2010
 (8.0)
 |
Updated in 2016
 (10.4)