Apache Commons Math 3.6.1 · org.apache.commons.math3.distribution.RealDistribution

Method Summary

Modifier and Type	Method and Description
public double	Returns: the probability that a random variable with this distribution takes a value less than or equal to `x` cumulativeProbability(double the point at which the CDF is evaluated x) For a random variable `X` whose values are distributed according to this distribution, this method returns `P(X <= x)`.
public double	Returns: the probability that a random variable with this distribution takes a value between `x0` and `x1`, excluding the lower and including the upper endpoint cumulativeProbability(double the exclusive lower bound x0, double the inclusive upper bound x1) Deprecated As of 3.1. In 4.0, this method will be renamed `probability(double x0, double x1)`. For a random variable `X` whose values are distributed according to this distribution, this method returns `P(x0 < X <= x1)`.
public double	Returns: the value of the probability density function at point `x` density(double the point at which the PDF is evaluated x) Returns the probability density function (PDF) of this distribution evaluated at the specified point `x`.
public double	Returns: the mean or `Double.NaN` if it is not defined getNumericalMean() Use this method to get the numerical value of the mean of this distribution.
public double	Returns: the variance (possibly `Double.POSITIVE_INFINITY` as for certain cases in `TDistribution`) or `Double.NaN` if it is not defined getNumericalVariance() Use this method to get the numerical value of the variance of this distribution.
public double	Returns: lower bound of the support (might be `Double.NEGATIVE_INFINITY`) getSupportLowerBound() Access the lower bound of the support.
public double	Returns: upper bound of the support (might be `Double.POSITIVE_INFINITY`) getSupportUpperBound() Access the upper bound of the support.
public double	Returns: the smallest `p`-quantile of this distribution (largest 0-quantile for `p = 0`) inverseCumulativeProbability(double the cumulative probability p) Computes the quantile function of this distribution.
public boolean	Returns: whether the support is connected or not isSupportConnected() Use this method to get information about whether the support is connected, i.e. whether all values between the lower and upper bound of the support are included in the support.
public boolean	Returns: true if the lower bound of support is finite and the density function returns a non-NaN, non-infinite value there isSupportLowerBoundInclusive() Deprecated to be removed in 4.0 Whether or not the lower bound of support is in the domain of the density function.
public boolean	Returns: true if the upper bound of support is finite and the density function returns a non-NaN, non-infinite value there isSupportUpperBoundInclusive() Deprecated to be removed in 4.0 Whether or not the upper bound of support is in the domain of the density function.
public double	Returns: the value of the probability mass function at point `x` probability(double the point at which the PMF is evaluated x) For a random variable `X` whose values are distributed according to this distribution, this method returns `P(X = x)`.
public void	reseedRandomGenerator(long the new seed seed) Reseed the random generator used to generate samples.
public double	Returns: a random value. sample() Generate a random value sampled from this distribution.
public double[]	Returns: an array representing the random sample sample(int the number of random values to generate sampleSize) Generate a random sample from the distribution.

Method Detail

cumulativeProbability back to summary

cumulativeProbability	back to summary
public double cumulativeProbability(double x) For a random variable `X` whose values are distributed according to this distribution, this method returns `P(X <= x)`. In other words, this method represents the (cumulative) distribution function (CDF) for this distribution. Parameters x:double the point at which the CDF is evaluated Returns:double the probability that a random variable with this distribution takes a value less than or equal to `x`

public double cumulativeProbability(double x)

For a random variable X whose values are distributed according to this distribution, this method returns P(X <= x). In other words, this method represents the (cumulative) distribution function (CDF) for this distribution.

Parameters

x:double: the point at which the CDF is evaluated

Returns:double

the probability that a random variable with this distribution takes a value less than or equal to x

cumulativeProbability back to summary

cumulativeProbability	back to summary
public double cumulativeProbability(double x0, double x1) throws NumberIsTooLargeException Deprecated As of 3.1. In 4.0, this method will be renamed `probability(double x0, double x1)`. For a random variable `X` whose values are distributed according to this distribution, this method returns `P(x0 < X <= x1)`. Parameters x0:double the exclusive lower bound x1:double the inclusive upper bound Returns:double the probability that a random variable with this distribution takes a value between `x0` and `x1`, excluding the lower and including the upper endpoint Annotations @Deprecated Exceptions NumberIsTooLargeException: if `x0 > x1`

public double cumulativeProbability(double x0, double x1) throws NumberIsTooLargeException

Deprecated

As of 3.1. In 4.0, this method will be renamed probability(double x0, double x1).

For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).

Parameters

x0:double: the exclusive lower bound
x1:double: the inclusive upper bound

Returns:double

the probability that a random variable with this distribution takes a value between x0 and x1, excluding the lower and including the upper endpoint

Annotations

@Deprecated

Exceptions

NumberIsTooLargeException:: if x0 > x1

density back to summary

density	back to summary
public double density(double x) Returns the probability density function (PDF) of this distribution evaluated at the specified point `x`. In general, the PDF is the derivative of the `CDF`. If the derivative does not exist at `x`, then an appropriate replacement should be returned, e.g. `Double.POSITIVE_INFINITY`, `Double.NaN`, or the limit inferior or limit superior of the difference quotient. Parameters x:double the point at which the PDF is evaluated Returns:double the value of the probability density function at point `x`

public double density(double x)

Returns the probability density function (PDF) of this distribution evaluated at the specified point x. In general, the PDF is the derivative of the CDF. If the derivative does not exist at x, then an appropriate replacement should be returned, e.g. Double.POSITIVE_INFINITY, Double.NaN, or the limit inferior or limit superior of the difference quotient.

Parameters

x:double: the point at which the PDF is evaluated

Returns:double

the value of the probability density function at point x

getNumericalMean back to summary

getNumericalMean	back to summary
public double getNumericalMean() Use this method to get the numerical value of the mean of this distribution. Returns:double the mean or `Double.NaN` if it is not defined

public double getNumericalMean()

Use this method to get the numerical value of the mean of this distribution.

Returns:double: the mean or Double.NaN if it is not defined

getNumericalVariance back to summary

getNumericalVariance	back to summary
public double getNumericalVariance() Use this method to get the numerical value of the variance of this distribution. Returns:double the variance (possibly `Double.POSITIVE_INFINITY` as for certain cases in `TDistribution`) or `Double.NaN` if it is not defined

public double getNumericalVariance()

Use this method to get the numerical value of the variance of this distribution.

Returns:double: the variance (possibly Double.POSITIVE_INFINITY as for certain cases in TDistribution) or Double.NaN if it is not defined

getSupportLowerBound back to summary

getSupportLowerBound	back to summary
public double getSupportLowerBound() Access the lower bound of the support. This method must return the same value as `inverseCumulativeProbability(0)`. In other words, this method must return `inf {x in R \| P(X <= x) > 0}`. Returns:double lower bound of the support (might be `Double.NEGATIVE_INFINITY`)

public double getSupportLowerBound()

Access the lower bound of the support. This method must return the same value as inverseCumulativeProbability(0). In other words, this method must return

inf {x in R | P(X <= x) > 0}.

Returns:double: lower bound of the support (might be Double.NEGATIVE_INFINITY)

getSupportUpperBound back to summary

getSupportUpperBound	back to summary
public double getSupportUpperBound() Access the upper bound of the support. This method must return the same value as `inverseCumulativeProbability(1)`. In other words, this method must return `inf {x in R \| P(X <= x) = 1}`. Returns:double upper bound of the support (might be `Double.POSITIVE_INFINITY`)

public double getSupportUpperBound()

Access the upper bound of the support. This method must return the same value as inverseCumulativeProbability(1). In other words, this method must return

inf {x in R | P(X <= x) = 1}.

Returns:double: upper bound of the support (might be Double.POSITIVE_INFINITY)

inverseCumulativeProbability back to summary

inverseCumulativeProbability	back to summary
public double inverseCumulativeProbability(double p) throws OutOfRangeException Computes the quantile function of this distribution. For a random variable `X` distributed according to this distribution, the returned value is `inf{x in R \| P(X<=x) >= p}` for `0 < p <= 1`, `inf{x in R \| P(X<=x) > 0}` for `p = 0`. Parameters p:double the cumulative probability Returns:double the smallest `p`-quantile of this distribution (largest 0-quantile for `p = 0`) Exceptions OutOfRangeException: if `p < 0` or `p > 1`

public double inverseCumulativeProbability(double p) throws OutOfRangeException

Computes the quantile function of this distribution. For a random variable X distributed according to this distribution, the returned value is

inf{x in R | P(X<=x) >= p} for 0 < p <= 1,
inf{x in R | P(X<=x) > 0} for p = 0.

Parameters

p:double: the cumulative probability

Returns:double

the smallest p-quantile of this distribution (largest 0-quantile for p = 0)

Exceptions

OutOfRangeException:: if p < 0 or p > 1

isSupportConnected	back to summary
public boolean isSupportConnected() Use this method to get information about whether the support is connected, i.e. whether all values between the lower and upper bound of the support are included in the support. Returns:boolean whether the support is connected or not

isSupportConnected

back to summary

public boolean isSupportConnected()

Use this method to get information about whether the support is connected, i.e. whether all values between the lower and upper bound of the support are included in the support.

Returns:boolean: whether the support is connected or not

isSupportLowerBoundInclusive back to summary

isSupportLowerBoundInclusive	back to summary
public boolean isSupportLowerBoundInclusive() Deprecated to be removed in 4.0 Whether or not the lower bound of support is in the domain of the density function. Returns true iff `getSupporLowerBound()` is finite and `density(getSupportLowerBound())` returns a non-NaN, non-infinite value. Returns:boolean true if the lower bound of support is finite and the density function returns a non-NaN, non-infinite value there Annotations @Deprecated

public boolean isSupportLowerBoundInclusive()

Deprecated

to be removed in 4.0

Whether or not the lower bound of support is in the domain of the density function. Returns true iff getSupporLowerBound() is finite and density(getSupportLowerBound()) returns a non-NaN, non-infinite value.

Returns:boolean

true if the lower bound of support is finite and the density function returns a non-NaN, non-infinite value there

Annotations

@Deprecated

isSupportUpperBoundInclusive back to summary

isSupportUpperBoundInclusive	back to summary
public boolean isSupportUpperBoundInclusive() Deprecated to be removed in 4.0 Whether or not the upper bound of support is in the domain of the density function. Returns true iff `getSupportUpperBound()` is finite and `density(getSupportUpperBound())` returns a non-NaN, non-infinite value. Returns:boolean true if the upper bound of support is finite and the density function returns a non-NaN, non-infinite value there Annotations @Deprecated

public boolean isSupportUpperBoundInclusive()

Deprecated

to be removed in 4.0

Whether or not the upper bound of support is in the domain of the density function. Returns true iff getSupportUpperBound() is finite and density(getSupportUpperBound()) returns a non-NaN, non-infinite value.

Returns:boolean

true if the upper bound of support is finite and the density function returns a non-NaN, non-infinite value there

Annotations

@Deprecated

probability back to summary

probability	back to summary
public double probability(double x) For a random variable `X` whose values are distributed according to this distribution, this method returns `P(X = x)`. In other words, this method represents the probability mass function (PMF) for the distribution. Parameters x:double the point at which the PMF is evaluated Returns:double the value of the probability mass function at point `x`

public double probability(double x)

For a random variable X whose values are distributed according to this distribution, this method returns P(X = x). In other words, this method represents the probability mass function (PMF) for the distribution.

Parameters

x:double: the point at which the PMF is evaluated

Returns:double

the value of the probability mass function at point x

reseedRandomGenerator	back to summary
public void reseedRandomGenerator(long seed) Reseed the random generator used to generate samples. Parameters seed:long the new seed

reseedRandomGenerator

back to summary

public void reseedRandomGenerator(long seed)

Reseed the random generator used to generate samples.

Parameters

seed:long: the new seed

sample	back to summary
public double sample() Generate a random value sampled from this distribution. Returns:double a random value.

sample

back to summary

public double sample()

Generate a random value sampled from this distribution.

Returns:double: a random value.

sample back to summary

sample	back to summary
public double[] sample(int sampleSize) Generate a random sample from the distribution. Parameters sampleSize:int the number of random values to generate Returns:double[] an array representing the random sample Exceptions NotStrictlyPositiveException: if `sampleSize` is not positive

public double[] sample(int sampleSize)

Generate a random sample from the distribution.

Parameters

sampleSize:int: the number of random values to generate

Returns:double[]

an array representing the random sample

Exceptions

NotStrictlyPositiveException:: if sampleSize is not positive

public Interface RealDistribution

Method Summary

Method Detail