public class ChiSquareDistribution extends Object implements ProbabilityDistribution
dchisq, pchisq, qchisq, rchisq.| Constructor and Description |
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ChiSquareDistribution(double k)
Construct a Chi-Square distribution.
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| Modifier and Type | Method and Description |
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double |
cdf(double x)
Gets the cumulative probability F(x) = Pr(X ≤ x).
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double |
density(double x)
The density function, which, if exists, is the derivative of F.
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double |
entropy()
Gets the entropy of this distribution.
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double |
kurtosis()
Gets the excess kurtosis of this distribution.
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double |
mean()
Gets the mean of this distribution.
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double |
median()
Gets the median of this distribution.
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double |
moment(double t)
The moment generating function is the expected value of etX.
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double |
quantile(double u)
Gets the quantile, the inverse of the cumulative distribution function.
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double |
skew()
Gets the skewness of this distribution.
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double |
variance()
Gets the variance of this distribution.
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public ChiSquareDistribution(double k)
k - the degree of freedompublic double mean()
ProbabilityDistributionmean in interface ProbabilityDistributionpublic double median()
ProbabilityDistributionmedian in interface ProbabilityDistributionpublic double variance()
ProbabilityDistributionvariance in interface ProbabilityDistributionpublic double skew()
ProbabilityDistributionskew in interface ProbabilityDistributionpublic double kurtosis()
ProbabilityDistributionkurtosis in interface ProbabilityDistributionpublic double entropy()
ProbabilityDistributionentropy in interface ProbabilityDistributionpublic double cdf(double x)
ProbabilityDistributioncdf in interface ProbabilityDistributionx - xpublic double quantile(double u)
ProbabilityDistributionThis may not always exist.F-1(u) = x, such that Pr(X ≤ x) = u
quantile in interface ProbabilityDistributionu - u, a quantilepublic double density(double x)
ProbabilityDistributionf(x) = dF(X) / dxThis may not always exist. For the discrete cases, this is the probability mass function. It gives the probability that a discrete random variable is exactly equal to some value.
density in interface ProbabilityDistributionx - xpublic double moment(double t)
ProbabilityDistributionE(etX)This may not always exist.
moment in interface ProbabilityDistributiont - tCopyright © 2010-2020 NM FinTech Ltd.. All Rights Reserved.