Class implements an interface of location scale distribution. More...

#include <scaleLocationDistribution.hpp>

Inheritance diagram for julian::ScaleLocationDistribution:

Public Member Functions
virtual double	getLocation ()=0
	returns location parameter More...

virtual double	getScale ()=0
	returns scale parameter More...

virtual double	getShape ()=0
	returns shape parameter More...

virtual void	setLocation (double)=0
	sets location parameter More...

virtual void	setScale (double)=0
	sets scale parameter More...

virtual void	setShape (double)=0
	sets shape parameter More...

virtual ProbabilityDistribution *	clone () const
	virtual copy constructor More...

virtual	~ScaleLocationDistribution ()
	destructor More...

Public Member Functions inherited from julian::ProbabilityDistribution
virtual double	CDF (double)=0
	calculates value of Cumulative Distribution Function More...

virtual double	PDF (double)=0
	calculates value of Probability Distribution Function More...

virtual double	invCDF (double)=0
	calculates quantile More...

virtual void	estimate (std::vector< double >)=0
	estimates parameters of random variables More...

virtual double	mean ()=0
	returns mean More...

virtual double	variance ()=0
	returns variance More...

virtual	~ProbabilityDistribution ()
	destructor More...

Detailed Description

Class implements an interface of location scale distribution.

In probability theory, especially in mathematical statistics, a location–scale family is a family of probability distributions parametrized by a location parameter and a non-negative scale parameter. If X, Y are two random variables whose distribution functions are members of the family, and assuming X has location = 0 and unit scale = 1 , then Y parametrized with location = $\lambda$ and scale = $\sigma$ can be written as Y = $\lambda$ + $\sigma$ X.

Location Scale Distribution is characterize by following parameters:

Location

$CDF(t - location | location) = CDF(t | 0.0)$

Scale

$CDF(t / scale | scale) = CDF(t | 1.0)$

Shape

Shape parameter is any parameter of a probability distribution that is neither a location parameter nor a scale parameter (nor a function of either or both of these only). Such a parameter must affect the shape of a distribution rather than simply shifting it (as a location parameter does) or stretching/shrinking it (as a scale parameter does).