umontreal.iro.lecuyer.probdist
Class LaplaceDist
- java.lang.Object
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- umontreal.iro.lecuyer.probdist.ContinuousDistribution
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- umontreal.iro.lecuyer.probdist.LaplaceDist
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- All Implemented Interfaces:
- Distribution
public class LaplaceDist extends ContinuousDistribution
Extends the classContinuousDistributionfor the Laplace distribution. It has location parameter μ and scale parameter β > 0. The density function is given byf (x) = e-| x-μ|/β/(2β) for - ∞ < x < ∞.The distribution function isand its inverse isF(x) = (1/2)e(x-μ)/β if x <= μ, F(x) = 1 - (1/2)e(μ-x)/β otherwise, F-1(u) = βlog(2u) + μ if 0 <= u <= 1/2, F-1(u) = μ - βlog(2(1 - u)) otherwise.
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Field Summary
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Fields inherited from class umontreal.iro.lecuyer.probdist.ContinuousDistribution
decPrec
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Constructor Summary
Constructors Constructor and Description LaplaceDist()Constructs a LaplaceDist object with default parameters μ = 0 and β = 1.LaplaceDist(double mu, double beta)Constructs a LaplaceDist object with parameters μ = mu and β = beta.
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method and Description doublebarF(double x)Returns the complementary distribution function.static doublebarF(double mu, double beta, double x)Computes the Laplace complementary distribution function.doublecdf(double x)Returns the distribution function F(x).static doublecdf(double mu, double beta, double x)Computes the Laplace distribution function.doubledensity(double x)Returns f (x), the density evaluated at x.static doubledensity(double mu, double beta, double x)Computes the Laplace density function.doublegetBeta()Returns the parameter β.static LaplaceDistgetInstanceFromMLE(double[] x, int n)Creates a new instance of a Laplace distribution with parameters μ and β estimated using the maximum likelihood method based on the n observations x[i], i = 0, 1,…, n - 1.doublegetMean()Returns the mean.static doublegetMean(double mu, double beta)Computes and returns the mean E[X] = μ of the Laplace distribution with parameters μ and β.static double[]getMLE(double[] x, int n)Estimates the parameters (μ, β) of the Laplace distribution using the maximum likelihood method, from the n observations x[i], i = 0, 1,…, n - 1.doublegetMu()Returns the parameter μ.double[]getParams()Return a table containing the parameters of the current distribution.doublegetStandardDeviation()Returns the standard deviation.static doublegetStandardDeviation(double mu, double beta)Computes and returns the standard deviation of the Laplace distribution with parameters μ and β.doublegetVariance()Returns the variance.static doublegetVariance(double mu, double beta)Computes and returns the variance Var[X] = 2β2 of the Laplace distribution with parameters μ and β.doubleinverseF(double u)Returns the inverse distribution function x = F-1(u).static doubleinverseF(double mu, double beta, double u)Computes the inverse Laplace distribution function.java.lang.StringtoString()-
Methods inherited from class umontreal.iro.lecuyer.probdist.ContinuousDistribution
getXinf, getXsup, inverseBisection, inverseBrent, setXinf, setXsup
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Constructor Detail
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LaplaceDist
public LaplaceDist()
Constructs a LaplaceDist object with default parameters μ = 0 and β = 1.
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LaplaceDist
public LaplaceDist(double mu, double beta)Constructs a LaplaceDist object with parameters μ = mu and β = beta.
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Method Detail
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density
public double density(double x)
Description copied from class:ContinuousDistributionReturns f (x), the density evaluated at x.- Specified by:
densityin classContinuousDistribution- Parameters:
x- value at which the density is evaluated- Returns:
- density function evaluated at x
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cdf
public double cdf(double x)
Description copied from interface:DistributionReturns the distribution function F(x).- Parameters:
x- value at which the distribution function is evaluated- Returns:
- distribution function evaluated at x
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barF
public double barF(double x)
Description copied from class:ContinuousDistributionReturns the complementary distribution function. The default implementation computes bar(F)(x) = 1 - F(x).- Specified by:
barFin interfaceDistribution- Overrides:
barFin classContinuousDistribution- Parameters:
x- value at which the complementary distribution function is evaluated- Returns:
- complementary distribution function evaluated at x
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inverseF
public double inverseF(double u)
Description copied from class:ContinuousDistributionReturns the inverse distribution function x = F-1(u). Restrictions: u∈[0, 1].- Specified by:
inverseFin interfaceDistribution- Overrides:
inverseFin classContinuousDistribution- Parameters:
u- value at which the inverse distribution function is evaluated- Returns:
- the inverse distribution function evaluated at u
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getMean
public double getMean()
Description copied from class:ContinuousDistributionReturns the mean.- Specified by:
getMeanin interfaceDistribution- Overrides:
getMeanin classContinuousDistribution- Returns:
- the mean
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getVariance
public double getVariance()
Description copied from class:ContinuousDistributionReturns the variance.- Specified by:
getVariancein interfaceDistribution- Overrides:
getVariancein classContinuousDistribution- Returns:
- the variance
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getStandardDeviation
public double getStandardDeviation()
Description copied from class:ContinuousDistributionReturns the standard deviation.- Specified by:
getStandardDeviationin interfaceDistribution- Overrides:
getStandardDeviationin classContinuousDistribution- Returns:
- the standard deviation
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density
public static double density(double mu, double beta, double x)Computes the Laplace density function.
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cdf
public static double cdf(double mu, double beta, double x)Computes the Laplace distribution function.
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barF
public static double barF(double mu, double beta, double x)Computes the Laplace complementary distribution function.
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inverseF
public static double inverseF(double mu, double beta, double u)Computes the inverse Laplace distribution function.
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getMLE
public static double[] getMLE(double[] x, int n)Estimates the parameters (μ, β) of the Laplace distribution using the maximum likelihood method, from the n observations x[i], i = 0, 1,…, n - 1. The estimates are returned in a two-element array, in regular order: [μ, β].- Parameters:
x- the list of observations used to evaluate parametersn- the number of observations used to evaluate parameters- Returns:
- returns the parameters [hat(μ), hat(β)]
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getInstanceFromMLE
public static LaplaceDist getInstanceFromMLE(double[] x, int n)
Creates a new instance of a Laplace distribution with parameters μ and β estimated using the maximum likelihood method based on the n observations x[i], i = 0, 1,…, n - 1.- Parameters:
x- the list of observations to use to evaluate parametersn- the number of observations to use to evaluate parameters
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getMean
public static double getMean(double mu, double beta)Computes and returns the mean E[X] = μ of the Laplace distribution with parameters μ and β.- Returns:
- the mean of the Laplace distribution E[X] = μ
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getVariance
public static double getVariance(double mu, double beta)Computes and returns the variance Var[X] = 2β2 of the Laplace distribution with parameters μ and β.- Returns:
- the variance of the Laplace distribution Var[X] = 2β2
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getStandardDeviation
public static double getStandardDeviation(double mu, double beta)Computes and returns the standard deviation of the Laplace distribution with parameters μ and β.- Returns:
- the standard deviation of the Laplace distribution
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getMu
public double getMu()
Returns the parameter μ.
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getBeta
public double getBeta()
Returns the parameter β.
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getParams
public double[] getParams()
Return a table containing the parameters of the current distribution. This table is put in regular order: [μ, β].
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toString
public java.lang.String toString()
- Overrides:
toStringin classjava.lang.Object
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