org.apache.commons.math.distribution
Class NormalDistributionImpl

java.lang.Object
  extended by org.apache.commons.math.distribution.AbstractDistribution
      extended by org.apache.commons.math.distribution.AbstractContinuousDistribution
          extended by 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.

Version:
$Revision: 1054524 $ $Date: 2011-01-03 05:59:18 +0100 (lun. 03 janv. 2011) $
See Also:
Serialized Form

Field Summary
static double DEFAULT_INVERSE_ABSOLUTE_ACCURACY
          Default inverse cumulative probability accuracy
private  double mean
          The mean of this distribution.
private static long serialVersionUID
          Serializable version identifier
private  double solverAbsoluteAccuracy
          Inverse cumulative probability accuracy
private static double SQRT2PI
          &sqrt;(2 π)
private  double standardDeviation
          The standard deviation of this distribution.
 
Fields inherited from class org.apache.commons.math.distribution.AbstractContinuousDistribution
randomData
 
Constructor Summary
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
 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.  
protected  double getDomainLowerBound(double p)
          Access the domain value lower bound, based on p, used to bracket a CDF root.
protected  double getDomainUpperBound(double p)
          Access the domain value upper bound, based on p, used to bracket a CDF root.
protected  double getInitialDomain(double p)
          Access the initial domain value, based on p, used to bracket a CDF root.
 double getMean()
          Access the mean.
 double getNumericalVariance()
          Returns the variance.
protected  double getSolverAbsoluteAccuracy()
          Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.
 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)
private  void setMeanInternal(double newMean)
          Modify the mean.
 void setStandardDeviation(double sd)
          Deprecated. as of 2.1 (class will become immutable in 3.0)
private  void setStandardDeviationInternal(double sd)
          Modify the standard deviation.
 
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
 

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

serialVersionUID

private static final long serialVersionUID
Serializable version identifier

See Also:
Constant Field Values

SQRT2PI

private static final double SQRT2PI
&sqrt;(2 π)


mean

private double mean
The mean of this distribution.


standardDeviation

private double standardDeviation
The standard deviation of this distribution.


solverAbsoluteAccuracy

private final double solverAbsoluteAccuracy
Inverse cumulative probability accuracy

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

setMeanInternal

private void setMeanInternal(double newMean)
Modify the mean.

Parameters:
newMean - 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.

setStandardDeviationInternal

private void setStandardDeviationInternal(double sd)
Modify the standard deviation.

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

getSolverAbsoluteAccuracy

protected double getSolverAbsoluteAccuracy()
Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.

Overrides:
getSolverAbsoluteAccuracy in class AbstractContinuousDistribution
Returns:
the solver absolute accuracy
Since:
2.1

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

getDomainLowerBound

protected double getDomainLowerBound(double p)
Access the domain value lower bound, based on p, used to bracket a CDF root. This method is used by inverseCumulativeProbability(double) to find critical values.

Specified by:
getDomainLowerBound in class AbstractContinuousDistribution
Parameters:
p - the desired probability for the critical value
Returns:
domain value lower bound, i.e. P(X < lower bound) < p

getDomainUpperBound

protected double getDomainUpperBound(double p)
Access the domain value upper bound, based on p, used to bracket a CDF root. This method is used by inverseCumulativeProbability(double) to find critical values.

Specified by:
getDomainUpperBound in class AbstractContinuousDistribution
Parameters:
p - the desired probability for the critical value
Returns:
domain value upper bound, i.e. P(X < upper bound) > p

getInitialDomain

protected double getInitialDomain(double p)
Access the initial domain value, based on p, used to bracket a CDF root. This method is used by inverseCumulativeProbability(double) to find critical values.

Specified by:
getInitialDomain in class AbstractContinuousDistribution
Parameters:
p - the desired probability for the critical value
Returns:
initial domain value

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


Copyright (c) 2003-2011 Apache Software Foundation