Class BinomialDistribution
- java.lang.Object
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- org.hipparchus.distribution.discrete.AbstractIntegerDistribution
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- org.hipparchus.distribution.discrete.BinomialDistribution
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- All Implemented Interfaces:
Serializable
,IntegerDistribution
public class BinomialDistribution extends AbstractIntegerDistribution
Implementation of the binomial distribution.
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Constructor Summary
Constructors Constructor Description BinomialDistribution(int trials, double p)
Create a binomial distribution with the given number of trials and probability of success.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description double
cumulativeProbability(int x)
For a random variableX
whose values are distributed according to this distribution, this method returnsP(X <= x)
.int
getNumberOfTrials()
Access the number of trials for this distribution.double
getNumericalMean()
Use this method to get the numerical value of the mean of this distribution.double
getNumericalVariance()
Use this method to get the numerical value of the variance of this distribution.double
getProbabilityOfSuccess()
Access the probability of success for this distribution.int
getSupportLowerBound()
Access the lower bound of the support.int
getSupportUpperBound()
Access the upper bound of the support.boolean
isSupportConnected()
Use this method to get information about whether the support is connected, i.e. whether all integers between the lower and upper bound of the support are included in the support.double
logProbability(int x)
For a random variableX
whose values are distributed according to this distribution, this method returnslog(P(X = x))
, wherelog
is the natural logarithm.double
probability(int x)
For a random variableX
whose values are distributed according to this distribution, this method returnsP(X = x)
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Methods inherited from class org.hipparchus.distribution.discrete.AbstractIntegerDistribution
inverseCumulativeProbability, probability, solveInverseCumulativeProbability
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Constructor Detail
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BinomialDistribution
public BinomialDistribution(int trials, double p) throws MathIllegalArgumentException
Create a binomial distribution with the given number of trials and probability of success.- Parameters:
trials
- Number of trials.p
- Probability of success.- Throws:
MathIllegalArgumentException
- iftrials < 0
.MathIllegalArgumentException
- ifp < 0
orp > 1
.
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Method Detail
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getNumberOfTrials
public int getNumberOfTrials()
Access the number of trials for this distribution.- Returns:
- the number of trials.
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getProbabilityOfSuccess
public double getProbabilityOfSuccess()
Access the probability of success for this distribution.- Returns:
- the probability of success.
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probability
public double probability(int x)
For a random variableX
whose values are distributed according to this distribution, this method returnsP(X = x)
. In other words, this method represents the probability mass function (PMF) for the distribution.- Parameters:
x
- the point at which the PMF is evaluated- Returns:
- the value of the probability mass function at
x
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logProbability
public double logProbability(int x)
For a random variableX
whose values are distributed according to this distribution, this method returnslog(P(X = x))
, wherelog
is the natural logarithm. In other words, this method represents the logarithm of the probability mass function (PMF) for the distribution. Note that due to the floating point precision and under/overflow issues, this method will for some distributions be more precise and faster than computing the logarithm ofIntegerDistribution.probability(int)
.The default implementation simply computes the logarithm of
probability(x)
.- Specified by:
logProbability
in interfaceIntegerDistribution
- Overrides:
logProbability
in classAbstractIntegerDistribution
- Parameters:
x
- the point at which the PMF is evaluated- Returns:
- the logarithm of the value of the probability mass function at
x
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cumulativeProbability
public double cumulativeProbability(int x)
For a random variableX
whose values are distributed according to this distribution, this method returnsP(X <= x)
. In other words, this method represents the (cumulative) distribution function (CDF) for this distribution.- Parameters:
x
- the point at which the CDF is evaluated- Returns:
- the probability that a random variable with this
distribution takes a value less than or equal to
x
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getNumericalMean
public double getNumericalMean()
Use this method to get the numerical value of the mean of this distribution. Forn
trials and probability parameterp
, the mean isn * p
.- Returns:
- the mean or
Double.NaN
if it is not defined
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getNumericalVariance
public double getNumericalVariance()
Use this method to get the numerical value of the variance of this distribution. Forn
trials and probability parameterp
, the variance isn * p * (1 - p)
.- Returns:
- the variance (possibly
Double.POSITIVE_INFINITY
orDouble.NaN
if it is not defined)
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getSupportLowerBound
public int getSupportLowerBound()
Access the lower bound of the support. This method must return the same value asinverseCumulativeProbability(0)
. In other words, this method must return
The lower bound of the support is always 0 except for the probability parameterinf {x in Z | P(X <= x) > 0}
.p = 1
.- Returns:
- lower bound of the support (0 or the number of trials)
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getSupportUpperBound
public int getSupportUpperBound()
Access the upper bound of the support. This method must return the same value asinverseCumulativeProbability(1)
. In other words, this method must return
The upper bound of the support is the number of trials except for the probability parameterinf {x in R | P(X <= x) = 1}
.p = 0
.- Returns:
- upper bound of the support (number of trials or 0)
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isSupportConnected
public boolean isSupportConnected()
Use this method to get information about whether the support is connected, i.e. whether all integers between the lower and upper bound of the support are included in the support. The support of this distribution is connected.- Returns:
true
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