Class BetaDistributionImpl
java.lang.Object
org.apache.commons.math.distribution.AbstractDistribution
org.apache.commons.math.distribution.AbstractContinuousDistribution
org.apache.commons.math.distribution.BetaDistributionImpl
- All Implemented Interfaces:
Serializable
,BetaDistribution
,ContinuousDistribution
,Distribution
,HasDensity<Double>
public class BetaDistributionImpl
extends AbstractContinuousDistribution
implements BetaDistribution
Implements the Beta distribution.
References:
- Since:
- 2.0
- Version:
- $Revision: 1054524 $ $Date: 2011-01-03 05:59:18 +0100 (lun. 03 janv. 2011) $
- See Also:
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Field Summary
FieldsModifier and TypeFieldDescriptionstatic final double
Default inverse cumulative probability accuracyFields inherited from class org.apache.commons.math.distribution.AbstractContinuousDistribution
randomData
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Constructor Summary
ConstructorsConstructorDescriptionBetaDistributionImpl
(double alpha, double beta) Build a new instance.BetaDistributionImpl
(double alpha, double beta, double inverseCumAccuracy) Build a new instance. -
Method Summary
Modifier and TypeMethodDescriptiondouble
cumulativeProbability
(double x) For a random variable X whose values are distributed according to this distribution, this method returns P(X ≤ x).double
cumulativeProbability
(double x0, double x1) For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).double
density
(double x) Return the probability density for a particular point.double
Deprecated.double
getAlpha()
Access the shape parameter, alphadouble
getBeta()
Access the shape parameter, betaprotected double
getDomainLowerBound
(double p) Access the domain value lower bound, based onp
, used to bracket a CDF root.protected double
getDomainUpperBound
(double p) Access the domain value upper bound, based onp
, used to bracket a CDF root.protected double
getInitialDomain
(double p) Access the initial domain value, based onp
, used to bracket a CDF root.double
Returns the mean.double
Returns the variance.protected double
Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.double
Returns the lower bound of the support for this distribution.double
Returns the upper bound of the support for this distribution.double
inverseCumulativeProbability
(double p) For this distribution, X, this method returns the critical point x, such that P(X < x) =p
.void
setAlpha
(double alpha) Deprecated.as of 2.1 (class will become immutable in 3.0)void
setBeta
(double beta) Deprecated.as of 2.1 (class will become immutable in 3.0)Methods inherited from class org.apache.commons.math.distribution.AbstractContinuousDistribution
reseedRandomGenerator, sample, sample
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Field Details
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DEFAULT_INVERSE_ABSOLUTE_ACCURACY
public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACYDefault inverse cumulative probability accuracy- Since:
- 2.1
- See Also:
-
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Constructor Details
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BetaDistributionImpl
public BetaDistributionImpl(double alpha, double beta, double inverseCumAccuracy) Build a new instance.- Parameters:
alpha
- first shape parameter (must be positive)beta
- second shape parameter (must be positive)inverseCumAccuracy
- the maximum absolute error in inverse cumulative probability estimates (defaults toDEFAULT_INVERSE_ABSOLUTE_ACCURACY
)- Since:
- 2.1
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BetaDistributionImpl
public BetaDistributionImpl(double alpha, double beta) Build a new instance.- Parameters:
alpha
- first shape parameter (must be positive)beta
- second shape parameter (must be positive)
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Method Details
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setAlpha
Deprecated.as of 2.1 (class will become immutable in 3.0)Modify the shape parameter, alpha.- Specified by:
setAlpha
in interfaceBetaDistribution
- Parameters:
alpha
- the new shape parameter.
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getAlpha
public double getAlpha()Access the shape parameter, alpha- Specified by:
getAlpha
in interfaceBetaDistribution
- Returns:
- alpha.
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setBeta
Deprecated.as of 2.1 (class will become immutable in 3.0)Modify the shape parameter, beta.- Specified by:
setBeta
in interfaceBetaDistribution
- Parameters:
beta
- the new scale parameter.
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getBeta
public double getBeta()Access the shape parameter, beta- Specified by:
getBeta
in interfaceBetaDistribution
- Returns:
- beta.
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density
Deprecated.Return the probability density for a particular point.- Specified by:
density
in interfaceBetaDistribution
- Specified by:
density
in interfaceHasDensity<Double>
- Parameters:
x
- The point at which the density should be computed.- Returns:
- The pdf at point x.
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density
public double density(double x) Return the probability density for a particular point.- Overrides:
density
in classAbstractContinuousDistribution
- Parameters:
x
- The point at which the density should be computed.- Returns:
- The pdf at point x.
- Since:
- 2.1
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inverseCumulativeProbability
For this distribution, X, this method returns the critical point x, such that P(X < x) =p
.- Specified by:
inverseCumulativeProbability
in interfaceContinuousDistribution
- Overrides:
inverseCumulativeProbability
in classAbstractContinuousDistribution
- Parameters:
p
- the desired probability- Returns:
- x, such that P(X < x) =
p
- Throws:
MathException
- if the inverse cumulative probability can not be computed due to convergence or other numerical errors.
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getInitialDomain
protected double getInitialDomain(double p) Access the initial domain value, based onp
, used to bracket a CDF root. This method is used byAbstractContinuousDistribution.inverseCumulativeProbability(double)
to find critical values.- Specified by:
getInitialDomain
in classAbstractContinuousDistribution
- Parameters:
p
- the desired probability for the critical value- Returns:
- initial domain value
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getDomainLowerBound
protected double getDomainLowerBound(double p) Access the domain value lower bound, based onp
, used to bracket a CDF root. This method is used byAbstractContinuousDistribution.inverseCumulativeProbability(double)
to find critical values.- Specified by:
getDomainLowerBound
in classAbstractContinuousDistribution
- Parameters:
p
- the desired probability for the critical value- Returns:
- domain value lower bound, i.e.
P(X < lower bound) <
p
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getDomainUpperBound
protected double getDomainUpperBound(double p) Access the domain value upper bound, based onp
, used to bracket a CDF root. This method is used byAbstractContinuousDistribution.inverseCumulativeProbability(double)
to find critical values.- Specified by:
getDomainUpperBound
in classAbstractContinuousDistribution
- Parameters:
p
- the desired probability for the critical value- Returns:
- domain value upper bound, i.e.
P(X < upper bound) >
p
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cumulativeProbability
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, or CDF, for this distribution.- Specified by:
cumulativeProbability
in interfaceDistribution
- Parameters:
x
- the value at which the distribution function is evaluated.- Returns:
- the probability that a random variable with this
distribution takes a value less than or equal to
x
- Throws:
MathException
- if the cumulative probability can not be computed due to convergence or other numerical errors.
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cumulativeProbability
For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).The default implementation uses the identity
P(x0 ≤ X ≤ x1) = P(X ≤ x1) - P(X ≤ x0)
- Specified by:
cumulativeProbability
in interfaceDistribution
- Overrides:
cumulativeProbability
in classAbstractDistribution
- Parameters:
x0
- the (inclusive) lower boundx1
- the (inclusive) upper bound- Returns:
- the probability that a random variable with this distribution
will take a value between
x0
andx1
, including the endpoints. - Throws:
MathException
- if the cumulative probability can not be computed due to convergence or other numerical errors.
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getSolverAbsoluteAccuracy
protected double getSolverAbsoluteAccuracy()Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.- Overrides:
getSolverAbsoluteAccuracy
in classAbstractContinuousDistribution
- Returns:
- the solver absolute accuracy
- Since:
- 2.1
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getSupportLowerBound
public double getSupportLowerBound()Returns the lower bound of the support for this distribution. The support of the Beta distribution is always [0, 1], regardless of the parameters, so this method always returns 0.- Returns:
- lower bound of the support (always 0)
- Since:
- 2.2
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getSupportUpperBound
public double getSupportUpperBound()Returns the upper bound of the support for this distribution. The support of the Beta distribution is always [0, 1], regardless of the parameters, so this method always returns 1.- Returns:
- lower bound of the support (always 1)
- Since:
- 2.2
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getNumericalMean
public double getNumericalMean()Returns the mean. For first shape parameters1
and second shape parameters2
, the mean iss1 / (s1 + s2)
- Returns:
- the mean
- Since:
- 2.2
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getNumericalVariance
public double getNumericalVariance()Returns the variance. For first shape parameters1
and second shape parameters2
, the variance is[ s1 * s2 ] / [ (s1 + s2)^2 * (s1 + s2 + 1) ]
- Returns:
- the variance
- Since:
- 2.2
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