org.apache.commons.math.distribution

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:

java.io.Serializable, ContinuousDistribution, Distribution, HasDensity<java.lang.Double>, NormalDistribution

public class NormalDistributionImpl
extends AbstractContinuousDistribution
implements NormalDistribution, java.io.Serializable

Default implementation of NormalDistribution.

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static double	DEFAULT_INVERSE_ABSOLUTE_ACCURACY Default inverse cumulative probability accuracy

Constructor Summary

Constructors

Constructor and Description
NormalDistributionImpl() Creates 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 Type	Method and Description
double	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	density(java.lang.Double x) Deprecated.
double	getMean() Access the mean.
double	getNumericalVariance() Returns the variance.
double	getStandardDeviation() Access the standard deviation.
double	getSupportLowerBound() Returns the lower bound of the support for the distribution.
double	getSupportUpperBound() 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

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.commons.math.distribution.Distribution

cumulativeProbability

Field Detail

DEFAULT_INVERSE_ABSOLUTE_ACCURACY

public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY

Default inverse cumulative probability accuracy

Since:

2.1

See Also:

Constant Field Values

Constructor Detail

NormalDistributionImpl

public NormalDistributionImpl(double mean,
                              double sd)

Create a normal distribution using the given mean and standard deviation.

Parameters:

mean - mean for this distribution

sd - standard deviation for this distribution

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 distribution

sd - standard deviation for this distribution

inverseCumAccuracy - inverse cumulative probability accuracy

Since:

2.1

NormalDistributionImpl

public NormalDistributionImpl()

Creates normal distribution with the mean equal to zero and standard deviation equal to one.

Method Detail

getMean

public double getMean()

Access the mean.

Specified by:

getMean in interface NormalDistribution

Returns:

mean for this distribution

setMean

@Deprecated
public void setMean(double mean)

Deprecated. as of 2.1 (class will become immutable in 3.0)

Modify the mean.

Specified by:

setMean in interface NormalDistribution

Parameters:

mean - for this distribution

getStandardDeviation

public double getStandardDeviation()

Access the standard deviation.

Specified by:

getStandardDeviation in interface NormalDistribution

Returns:

standard deviation for this distribution

setStandardDeviation

@Deprecated
public void setStandardDeviation(double sd)

Deprecated. as of 2.1 (class will become immutable in 3.0)

Modify the standard deviation.

Specified by:

setStandardDeviation in interface NormalDistribution

Parameters:

sd - standard deviation for this distribution

Throws:

java.lang.IllegalArgumentException - if sd is not positive.

density

@Deprecated
public double density(java.lang.Double x)

Deprecated.

Return the probability density for a particular point.

Specified by:

density in interface HasDensity<java.lang.Double>

Specified by:

density in interface NormalDistribution

Parameters:

x - The point at which the density should be computed.

Returns:

The pdf at point x.

density

public double density(double x)

Returns the probability density for a particular point.

Overrides:

density in class AbstractContinuousDistribution

Parameters:

x - The point at which the density should be computed.

Returns:

The pdf at point x.

Since:

2.1

cumulativeProbability

public double cumulativeProbability(double x)
                             throws MathException

For this distribution, X, this method returns P(X < x). If xis more than 40 standard deviations from the mean, 0 or 1 is returned, as in these cases the actual value is within Double.MIN_VALUE of 0 or 1.

Specified by:

cumulativeProbability in interface Distribution

Parameters:

x - the value at which the CDF is evaluated.

Returns:

CDF evaluated at x.

Throws:

MathException - if the algorithm fails to converge

inverseCumulativeProbability

public double inverseCumulativeProbability(double p)
                                    throws MathException

For this distribution, X, this method returns the critical point x, such that P(X < x) = p.

Returns Double.NEGATIVE_INFINITY for p=0 and Double.POSITIVE_INFINITY for p=1.

Specified by:

inverseCumulativeProbability in interface ContinuousDistribution

Overrides:

inverseCumulativeProbability in class AbstractContinuousDistribution

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.

java.lang.IllegalArgumentException - if p is not a valid probability.

sample

public double sample()
              throws MathException

Generates a random value sampled from this distribution.

Overrides:

sample in class AbstractContinuousDistribution

Returns:

random value

Throws:

MathException - if an error occurs generating the random value

Since:

2.2

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

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

getNumericalVariance

public double getNumericalVariance()

Returns the variance. For standard deviation parameter s, the variance is s^2

Returns:

the variance

Since:

2.2