org.apache.commons.math.distribution
Class ExponentialDistributionImpl

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.ExponentialDistributionImpl
All Implemented Interfaces:
Serializable, ContinuousDistribution, Distribution, ExponentialDistribution, HasDensity<Double>

public class ExponentialDistributionImpl
extends AbstractContinuousDistribution
implements ExponentialDistribution, Serializable

The default implementation of ExponentialDistribution.

See Also:
Serialized Form

Field Summary
static double DEFAULT_INVERSE_ABSOLUTE_ACCURACY
          Default inverse cumulative probability accuracy
 
Constructor Summary
ExponentialDistributionImpl(double mean)
          Create a exponential distribution with the given mean.
ExponentialDistributionImpl(double mean, double inverseCumAccuracy)
          Create a exponential distribution with the given mean.
 
Method Summary
 double cumulativeProbability(double x)
          For this distribution, X, this method returns P(X < x).
 double density(double x)
          Return the probability density for a particular point.
 double density(Double x)
          Deprecated. - use density(double)
 double getMean()
          Access the mean.
 double getNumericalMean()
          Returns the mean of the distribution.
 double getNumericalVariance()
          Returns the variance of the distribution.
 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)
 
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

ExponentialDistributionImpl

public ExponentialDistributionImpl(double mean)
Create a exponential distribution with the given mean.

Parameters:
mean - mean of this distribution.

ExponentialDistributionImpl

public ExponentialDistributionImpl(double mean,
                                   double inverseCumAccuracy)
Create a exponential distribution with the given mean.

Parameters:
mean - mean of this distribution.
inverseCumAccuracy - the maximum absolute error in inverse cumulative probability estimates (defaults to DEFAULT_INVERSE_ABSOLUTE_ACCURACY)
Since:
2.1
Method Detail

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 ExponentialDistribution
Parameters:
mean - the new mean.
Throws:
IllegalArgumentException - if mean is not positive.

getMean

public double getMean()
Access the mean.

Specified by:
getMean in interface ExponentialDistribution
Returns:
the mean.

density

@Deprecated
public double density(Double x)
Deprecated. - use density(double)

Return the probability density for a particular point.

Specified by:
density in interface ExponentialDistribution
Specified by:
density in interface HasDensity<Double>
Parameters:
x - The point at which the density should be computed.
Returns:
The pdf at point x.

density

public double density(double x)
Return 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). The implementation of this method is based on:

Specified by:
cumulativeProbability in interface Distribution
Parameters:
x - the value at which the CDF is evaluated.
Returns:
CDF for this distribution.
Throws:
MathException - if the cumulative probability can not be computed due to convergence or other numerical errors.

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 0 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.
IllegalArgumentException - if p < 0 or p > 1.

sample

public double sample()
              throws MathException
Generates a random value sampled from this distribution.

Algorithm Description: Uses the Inversion Method to generate exponentially distributed random values from uniform deviates.

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 0, regardless of the mean.

Returns:
lower bound of the support (always 0)
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, regardless of the mean.

Returns:
upper bound of the support (always Double.POSITIVE_INFINITY)
Since:
2.2

getNumericalMean

public double getNumericalMean()
Returns the mean of the distribution. For mean parameter k, the mean is k

Returns:
the mean
Since:
2.2

getNumericalVariance

public double getNumericalVariance()
Returns the variance of the distribution. For mean parameter k, the variance is k^2

Returns:
the variance
Since:
2.2


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