Class NormalDistributionImpl
java.lang.Object
org.apache.commons.math.distribution.AbstractDistribution
org.apache.commons.math.distribution.AbstractContinuousDistribution
org.apache.commons.math.distribution.NormalDistributionImpl
- All Implemented Interfaces:
Serializable
,ContinuousDistribution
,Distribution
,HasDensity<Double>
,NormalDistribution
public class NormalDistributionImpl
extends AbstractContinuousDistribution
implements NormalDistribution, Serializable
Default implementation of
NormalDistribution
.- 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
ConstructorsConstructorDescriptionCreates normal distribution with the mean equal to zero and standard deviation equal to one.NormalDistributionImpl
(double mean, double sd) Create a normal distribution using the given mean and standard deviation.NormalDistributionImpl
(double mean, double sd, double inverseCumAccuracy) Create a normal distribution using the given mean, standard deviation and inverse cumulative distribution accuracy. -
Method Summary
Modifier and TypeMethodDescriptiondouble
cumulativeProbability
(double x) For this distribution, X, this method returns P(X <x
).double
density
(double x) Returns the probability density for a particular point.double
Deprecated.protected 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
getMean()
Access the mean.double
Returns the variance.protected double
Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.double
Access the standard deviation.double
Returns the lower bound of the support for the distribution.double
Returns the upper bound of the support for the distribution.double
inverseCumulativeProbability
(double p) For this distribution, X, this method returns the critical point x, such that P(X < x) =p
.double
sample()
Generates a random value sampled from this distribution.void
setMean
(double mean) Deprecated.as of 2.1 (class will become immutable in 3.0)void
setStandardDeviation
(double sd) Deprecated.as of 2.1 (class will become immutable in 3.0)Methods inherited from class org.apache.commons.math.distribution.AbstractContinuousDistribution
reseedRandomGenerator, sample
Methods inherited from class org.apache.commons.math.distribution.AbstractDistribution
cumulativeProbability
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
Methods inherited from interface org.apache.commons.math.distribution.Distribution
cumulativeProbability
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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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NormalDistributionImpl
public NormalDistributionImpl(double mean, double sd) Create a normal distribution using the given mean and standard deviation.- Parameters:
mean
- mean for this distributionsd
- standard deviation for this distribution
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NormalDistributionImpl
public NormalDistributionImpl(double mean, double sd, double inverseCumAccuracy) Create a normal distribution using the given mean, standard deviation and inverse cumulative distribution accuracy.- Parameters:
mean
- mean for this distributionsd
- standard deviation for this distributioninverseCumAccuracy
- inverse cumulative probability accuracy- Since:
- 2.1
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NormalDistributionImpl
public NormalDistributionImpl()Creates normal distribution with the mean equal to zero and standard deviation equal to one.
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Method Details
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getMean
public double getMean()Access the mean.- Specified by:
getMean
in interfaceNormalDistribution
- Returns:
- mean for this distribution
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setMean
Deprecated.as of 2.1 (class will become immutable in 3.0)Modify the mean.- Specified by:
setMean
in interfaceNormalDistribution
- Parameters:
mean
- for this distribution
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getStandardDeviation
public double getStandardDeviation()Access the standard deviation.- Specified by:
getStandardDeviation
in interfaceNormalDistribution
- Returns:
- standard deviation for this distribution
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setStandardDeviation
Deprecated.as of 2.1 (class will become immutable in 3.0)Modify the standard deviation.- Specified by:
setStandardDeviation
in interfaceNormalDistribution
- Parameters:
sd
- standard deviation for this distribution- Throws:
IllegalArgumentException
- ifsd
is not positive.
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density
Deprecated.Return the probability density for a particular point.- Specified by:
density
in interfaceHasDensity<Double>
- Specified by:
density
in interfaceNormalDistribution
- 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) Returns 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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cumulativeProbability
For this distribution, X, this method returns P(X <x
). Ifx
is more than 40 standard deviations from the mean, 0 or 1 is returned, as in these cases the actual value is withinDouble.MIN_VALUE
of 0 or 1.- Specified by:
cumulativeProbability
in interfaceDistribution
- Parameters:
x
- the value at which the CDF is evaluated.- Returns:
- CDF evaluated at
x
. - Throws:
MathException
- if the algorithm fails to converge
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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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inverseCumulativeProbability
For this distribution, X, this method returns the critical point x, such that P(X < x) =p
.Returns
Double.NEGATIVE_INFINITY
for p=0 andDouble.POSITIVE_INFINITY
for p=1.- 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.IllegalArgumentException
- ifp
is not a valid probability.
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sample
Generates a random value sampled from this distribution.- Overrides:
sample
in classAbstractContinuousDistribution
- Returns:
- random value
- Throws:
MathException
- if an error occurs generating the random value- Since:
- 2.2
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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 byinverseCumulativeProbability(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 byinverseCumulativeProbability(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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getInitialDomain
protected double getInitialDomain(double p) Access the initial domain value, based onp
, used to bracket a CDF root. This method is used byinverseCumulativeProbability(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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getSupportLowerBound
public double getSupportLowerBound()Returns the lower bound of the support for the distribution. The lower bound of the support is always negative infinity no matter the parameters.- Returns:
- lower bound of the support (always Double.NEGATIVE_INFINITY)
- Since:
- 2.2
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getSupportUpperBound
public double getSupportUpperBound()Returns the upper bound of the support for the distribution. The upper bound of the support is always positive infinity no matter the parameters.- Returns:
- upper bound of the support (always Double.POSITIVE_INFINITY)
- Since:
- 2.2
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getNumericalVariance
public double getNumericalVariance()Returns the variance. For standard deviation parameters
, the variance iss^2
- Returns:
- the variance
- Since:
- 2.2
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