com.opengamma.strata.math.impl.cern

Class Normal

java.lang.Object

com.opengamma.strata.math.impl.cern.Normal

All Implemented Interfaces:

Serializable, Cloneable, DoubleUnaryOperator, IntUnaryOperator

public class Normal
extends Object

Normal (aka Gaussian) distribution; See the math definition and animated definition.

                       
                                   1                       2
          pdf(x) = ---------    exp( - (x-mean) / 2v ) 
                           sqrt(2pi*v)

                                                        x
                                                         -
                                   1        | |                 2
          cdf(x) = ---------    |    exp( - (t-mean) / 2v ) dt
                           sqrt(2pi*v)| |
                                                   -
                                                  -inf.

where v = variance = standardDeviation^2.

Instance methods operate on a user supplied uniform random number generator; they are unsynchronized.

Static methods operate on a default uniform random number generator; they are synchronized.

Implementation: Polar Box-Muller transformation. See G.E.P. Box, M.E. Muller (1958): A note on the generation of random normal deviates, Annals Math. Statist. 29, 610-611.

Version:

1.0, 09/24/99

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected double	cache
protected boolean	cacheFilled
protected double	mean
protected RandomEngine	randomGenerator
protected static Normal	shared
protected double	SQRT_INV
protected double	standardDeviation
protected double	variance

Constructor Summary

Constructors

Constructor and Description
Normal(double mean, double standardDeviation, RandomEngine randomGenerator) Constructs a normal (gauss) distribution.

Method Summary

Modifier and Type	Method and Description
double	applyAsDouble(double dummy) Equivalent to nextDouble().
int	applyAsInt(int dummy) Equivalent to nextInt().
double	cdf(double x) Returns the cumulative distribution function.
Object	clone() Returns a deep copy of the receiver; the copy will produce identical sequences.
protected RandomEngine	getRandomGenerator() Returns the used uniform random number generator;
static RandomEngine	makeDefaultGenerator() Constructs and returns a new uniform random number generation engine seeded with the current time.
double	nextDouble() Returns a random number from the distribution.
double	nextDouble(double mean, double standardDeviation) Returns a random number from the distribution; bypasses the internal state.
int	nextInt() Returns a random number from the distribution; returns (int) Math.round(nextDouble()).
double	pdf(double x) Returns the probability distribution function.
protected void	setRandomGenerator(RandomEngine randomGenerator) Sets the uniform random generator internally used.
void	setState(double mean, double standardDeviation) Sets the mean and variance.
static double	staticNextDouble(double mean, double standardDeviation) Returns a random number from the distribution with the given mean and standard deviation.
String	toString() Returns a String representation of the receiver.

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.util.function.DoubleUnaryOperator

andThen, compose, identity

Methods inherited from interface java.util.function.IntUnaryOperator

andThen, compose, identity

Field Detail

mean

protected double mean

variance

protected double variance

standardDeviation

protected double standardDeviation

cache

protected double cache

cacheFilled

protected boolean cacheFilled

SQRT_INV

protected double SQRT_INV

shared

protected static Normal shared

randomGenerator

protected RandomEngine randomGenerator

Constructor Detail

Normal

public Normal(double mean,
              double standardDeviation,
              RandomEngine randomGenerator)

Constructs a normal (gauss) distribution. Example: mean=0.0, standardDeviation=1.0.

Parameters:

mean - mean

standardDeviation - standard deviation

randomGenerator - generator

Method Detail

cdf

public double cdf(double x)

Returns the cumulative distribution function.

Parameters:

x - x

Returns:

result

nextDouble

public double nextDouble()

Returns a random number from the distribution.

Returns:

result

nextDouble

public double nextDouble(double mean,
                         double standardDeviation)

Returns a random number from the distribution; bypasses the internal state.

Parameters:

mean - mean

standardDeviation - standard deviation

Returns:

result

pdf

public double pdf(double x)

Returns the probability distribution function.

Parameters:

x - x

Returns:

result

setRandomGenerator

protected void setRandomGenerator(RandomEngine randomGenerator)

Sets the uniform random generator internally used.

Parameters:

randomGenerator - input

setState

public void setState(double mean,
                     double standardDeviation)

Sets the mean and variance.

Parameters:

mean - mean

standardDeviation - standard deviation

staticNextDouble

public static double staticNextDouble(double mean,
                                      double standardDeviation)

Returns a random number from the distribution with the given mean and standard deviation.

Parameters:

mean - mean

standardDeviation - standard deviation

Returns:

result

toString

public String toString()

Returns a String representation of the receiver.

Overrides:

toString in class Object

applyAsDouble

public double applyAsDouble(double dummy)

Equivalent to nextDouble(). This has the effect that distributions can now be used as function objects, returning a random number upon function evaluation.

Specified by:

applyAsDouble in interface DoubleUnaryOperator

applyAsInt

public int applyAsInt(int dummy)

Equivalent to nextInt(). This has the effect that distributions can now be used as function objects, returning a random number upon function evaluation.

Specified by:

applyAsInt in interface IntUnaryOperator

clone

public Object clone()

Returns a deep copy of the receiver; the copy will produce identical sequences. After this call has returned, the copy and the receiver have equal but separate state.

Returns:

a copy of the receiver.

getRandomGenerator

protected RandomEngine getRandomGenerator()

Returns the used uniform random number generator;

Returns:

result

makeDefaultGenerator

public static RandomEngine makeDefaultGenerator()

Constructs and returns a new uniform random number generation engine seeded with the current time. Currently this is MersenneTwister.

Returns:

result

nextInt

public int nextInt()

Returns a random number from the distribution; returns (int) Math.round(nextDouble()). Override this method if necessary.

Returns:

result