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java.lang.Objectumontreal.iro.lecuyer.probdist.ContinuousDistribution
umontreal.iro.lecuyer.probdist.HyperbolicSecantDist
public class HyperbolicSecantDist
Extends the class ContinuousDistribution
for
the Hyperbolic Secant distribution with location
parameter μ and scale parameter
σ > 0.
Its density is
The non-static versions of the methods cdf, barF, and inverseF call the static version of the same name.
Field Summary |
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Fields inherited from class umontreal.iro.lecuyer.probdist.ContinuousDistribution |
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decPrec |
Constructor Summary | |
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HyperbolicSecantDist(double mu,
double sigma)
Constructs a hyperbolic secant distribution with parameters μ and σ. |
Method Summary | |
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double |
barF(double x)
Returns bar(F)(x) = 1 - F(x). |
static double |
barF(double mu,
double sigma,
double x)
Computes the complementary distribution function of the hyperbolic secant distribution with parameters μ and σ. |
double |
cdf(double x)
Computes and returns the distribution function F(x). |
static double |
cdf(double mu,
double sigma,
double x)
Computes the distribution function of the hyperbolic secant distribution with parameters μ and σ. |
double |
density(double x)
Returns f (x), the density of X evaluated at x. |
static double |
density(double mu,
double sigma,
double x)
Computes the density function for a hyperbolic secant distribution with parameters μ and σ. |
static HyperbolicSecantDist |
getInstanceFromMLE(double[] x,
int n)
Creates a new instance of a hyperbolic secant distribution with parameters μ and σ estimated using the maximum likelihood method based on the n observations in table x[i], i = 0, 1,…, n - 1. |
static double[] |
getMaximumLikelihoodEstimate(double[] x,
int n)
Estimates and returns the parameters [hat(μ), hat(σ)] of the hyperbolic secant distribution using the maximum likelihood method based on the n observations in table x[i], i = 0, 1,…, n - 1. |
double |
getMean()
Returns the mean of the distribution function. |
static double |
getMean(double mu,
double sigma)
Computes and returns the mean E[X] = μ of the hyperbolic secant distribution with parameters μ and σ. |
double |
getMu()
Returns the parameter μ of this object. |
double |
getSigma()
Returns the parameter σ of this object. |
double |
getStandardDeviation()
Returns the standard deviation of the distribution function. |
static double |
getStandardDeviation(double mu,
double sigma)
Computes and returns the standard deviation of the hyperbolic secant distribution with parameters μ and σ. |
double |
getVariance()
Returns the variance of the distribution function. |
static double |
getVariance(double mu,
double sigma)
Computes and returns the variance Var[X] = σ2 of the hyperbolic secant distribution with parameters μ and σ. |
double |
inverseF(double u)
Computes and returns the inverse distribution function F-1(u), defined in. |
static double |
inverseF(double mu,
double sigma,
double u)
Computes the inverse of the hyperbolic secant distribution with parameters μ and σ. |
void |
setParams(double mu,
double sigma)
Sets the parameters μ and σ of this object. |
Methods inherited from class umontreal.iro.lecuyer.probdist.ContinuousDistribution |
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inverseBisection, inverseBrent |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public HyperbolicSecantDist(double mu, double sigma)
Method Detail |
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public double density(double x)
ContinuousDistribution
density
in class ContinuousDistribution
x
- value at which the density is evaluated
public double cdf(double x)
Distribution
x
- value at which the distribution function is evaluated
public double barF(double x)
Distribution
barF
in interface Distribution
barF
in class ContinuousDistribution
x
- value at which the complementary distribution function is evaluated
public double inverseF(double u)
Distribution
inverseF
in interface Distribution
inverseF
in class ContinuousDistribution
u
- value in the interval (0, 1) for which the inverse
distribution function is evaluated
public double getMean()
Distribution
public double getVariance()
Distribution
public double getStandardDeviation()
Distribution
public static double density(double mu, double sigma, double x)
public static double cdf(double mu, double sigma, double x)
public static double barF(double mu, double sigma, double x)
public static double inverseF(double mu, double sigma, double u)
public static HyperbolicSecantDist getInstanceFromMLE(double[] x, int n)
x
- the list of observations to use to evaluate parametersn
- the number of observations to use to evaluate parameterspublic static double[] getMaximumLikelihoodEstimate(double[] x, int n)
x
- the list of observations to use to evaluate parametersn
- the number of observations to use to evaluate parameters
public static double getMean(double mu, double sigma)
public static double getVariance(double mu, double sigma)
public static double getStandardDeviation(double mu, double sigma)
public double getMu()
public double getSigma()
public void setParams(double mu, double sigma)
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