@PublicationReference(author="Wikipedia", title="Logistic distribution", type=WebPage, year=2011, url="http://en.wikipedia.org/wiki/Logistic_distribution") public class LogisticDistribution extends AbstractClosedFormSmoothUnivariateDistribution
Modifier and Type | Class and Description |
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static class |
LogisticDistribution.CDF
CDF of the LogisticDistribution
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static class |
LogisticDistribution.PDF
PDF of the LogisticDistribution
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Modifier and Type | Field and Description |
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static double |
DEFAULT_MEAN
Default mean, 0.0.
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static double |
DEFAULT_SCALE
Default scale, 1.0.
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protected double |
mean
Mean (median and mode) of the distribution.
|
protected double |
scale
Scale of the distribution, proportionate to the standard deviation,
must be greater than zero.
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Constructor and Description |
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LogisticDistribution()
Default constructor
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LogisticDistribution(double mean,
double scale)
Creates a new instance of LogisticDistribution
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LogisticDistribution(LogisticDistribution other)
Copy constructor
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Modifier and Type | Method and Description |
---|---|
LogisticDistribution |
clone()
This makes public the clone method on the
Object class and
removes the exception that it throws. |
void |
convertFromVector(Vector parameters)
Converts the object from a Vector of parameters.
|
Vector |
convertToVector()
Converts the object to a vector.
|
LogisticDistribution.CDF |
getCDF()
Gets the CDF of a scalar distribution.
|
java.lang.Double |
getMaxSupport()
Gets the minimum support (domain or input) of the distribution.
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double |
getMeanAsDouble()
Gets the mean of the distribution as a double.
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java.lang.Double |
getMinSupport()
Gets the minimum support (domain or input) of the distribution.
|
LogisticDistribution.PDF |
getProbabilityFunction()
Gets the distribution function associated with this Distribution,
either the PDF or PMF.
|
double |
getScale()
Getter for scale
|
double |
getVariance()
Gets the variance of the distribution.
|
double |
sampleAsDouble(java.util.Random random)
Samples a value from this distribution as a double.
|
void |
sampleInto(java.util.Random random,
double[] output,
int start,
int length)
Samples values from this distribution as an array of doubles.
|
void |
setMean(double mean)
Setter for mean
|
void |
setScale(double scale)
Setter for scale
|
getMean, sampleAsDoubles, sampleInto
sample, sample
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
sample, sample
public static final double DEFAULT_MEAN
public static final double DEFAULT_SCALE
protected double mean
protected double scale
public LogisticDistribution()
public LogisticDistribution(double mean, double scale)
mean
- Mean (median and mode) of the distribution.scale
- Scale of the distribution, proportionate to the standard deviation,
must be greater than zero.public LogisticDistribution(LogisticDistribution other)
other
- LogisticDistribution to copypublic LogisticDistribution clone()
AbstractCloneableSerializable
Object
class and
removes the exception that it throws. Its default behavior is to
automatically create a clone of the exact type of object that the
clone is called on and to copy all primitives but to keep all references,
which means it is a shallow copy.
Extensions of this class may want to override this method (but call
super.clone()
to implement a "smart copy". That is, to target
the most common use case for creating a copy of the object. Because of
the default behavior being a shallow copy, extending classes only need
to handle fields that need to have a deeper copy (or those that need to
be reset). Some of the methods in ObjectUtil
may be helpful in
implementing a custom clone method.
Note: The contract of this method is that you must use
super.clone()
as the basis for your implementation.clone
in interface Vectorizable
clone
in interface CloneableSerializable
clone
in class AbstractClosedFormUnivariateDistribution<java.lang.Double>
public double sampleAsDouble(java.util.Random random)
SmoothUnivariateDistribution
sampleAsDouble
in interface SmoothUnivariateDistribution
sampleAsDouble
in class AbstractClosedFormSmoothUnivariateDistribution
random
- Random number generator to use.public void sampleInto(java.util.Random random, double[] output, int start, int length)
SmoothUnivariateDistribution
random
- Random number generator to use.output
- The array to write the result into. Cannot be null.start
- The offset in the array to start writing at. Cannot be negative.length
- The number of values to sample. Cannot be negative.public Vector convertToVector()
Vectorizable
public void convertFromVector(Vector parameters)
Vectorizable
parameters
- The parameters to incorporate.public java.lang.Double getMinSupport()
UnivariateDistribution
public java.lang.Double getMaxSupport()
UnivariateDistribution
public double getVariance()
UnivariateDistribution
public LogisticDistribution.PDF getProbabilityFunction()
ComputableDistribution
public LogisticDistribution.CDF getCDF()
UnivariateDistribution
public double getMeanAsDouble()
UnivariateDistribution
public void setMean(double mean)
mean
- Mean (median and mode) of the distribution.public double getScale()
public void setScale(double scale)
scale
- Scale of the distribution, proportionate to the standard deviation,
must be greater than zero.