Package dev.nm.stat.evt.evd.univariate
Class OrderStatisticsDistribution
- java.lang.Object
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- dev.nm.stat.evt.evd.univariate.OrderStatisticsDistribution
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- All Implemented Interfaces:
ProbabilityDistribution,UnivariateEVD
public class OrderStatisticsDistribution extends Object implements UnivariateEVD
The asymptotic nondegenerate distributions of the r-th smallest (largest) order statistic. The R equivalent functions areevd::dorder,evd::porder,evd::rorder.
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Constructor Summary
Constructors Constructor Description OrderStatisticsDistribution(ProbabilityDistribution dist, int nIIDs, int order)Create an instance with the probability distribution of \(X\), the number of iid samples to be drawn, and the order statistic.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description doublecdf(double x)Gets the cumulative probability F(x) = Pr(X ≤ x).doubledensity(double x)The density function, which, if exists, is the derivative of F.doubleentropy()Gets the entropy of this distribution.doublekurtosis()Gets the excess kurtosis of this distribution.doublelogDensity(double x)Get the logarithm of the probability density function at \(x\), that is, \(\log(f(x))\).doublemean()Gets the mean of this distribution.doublemedian()Gets the median of this distribution.doublemoment(double x)The moment generating function is the expected value of etX.doublequantile(double x)Gets the quantile, the inverse of the cumulative distribution function.doubleskew()Gets the skewness of this distribution.doublevariance()Gets the variance of this distribution.
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Constructor Detail
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OrderStatisticsDistribution
public OrderStatisticsDistribution(ProbabilityDistribution dist, int nIIDs, int order)
Create an instance with the probability distribution of \(X\), the number of iid samples to be drawn, and the order statistic.- Parameters:
dist- the probability distributionnIIDs- the number of independent variablesorder- the order statistic (largest) (1 means smallest, n means largest)
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Method Detail
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density
public double density(double x)
Description copied from interface:ProbabilityDistributionThe density function, which, if exists, is the derivative of F. It describes the density of probability at each point in the sample space.f(x) = dF(X) / dx
This 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.- Specified by:
densityin interfaceProbabilityDistribution- Parameters:
x- x- Returns:
- f(x)
- See Also:
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logDensity
public double logDensity(double x)
Description copied from interface:UnivariateEVDGet the logarithm of the probability density function at \(x\), that is, \(\log(f(x))\).- Specified by:
logDensityin interfaceUnivariateEVD- Parameters:
x- \(x\)- Returns:
- \(\log(f(x))\)
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cdf
public double cdf(double x)
Description copied from interface:ProbabilityDistributionGets the cumulative probability F(x) = Pr(X ≤ x).- Specified by:
cdfin interfaceProbabilityDistribution- Parameters:
x- x- Returns:
- F(x) = Pr(X ≤ x)
- See Also:
- Wikipedia: Cumulative distribution function
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quantile
public double quantile(double x)
Description copied from interface:ProbabilityDistributionGets the quantile, the inverse of the cumulative distribution function. It is the value below which random draws from the distribution would fall u×100 percent of the time.
This may not always exist.F-1(u) = x, such that Pr(X ≤ x) = u
- Specified by:
quantilein interfaceProbabilityDistribution- Parameters:
x-u, a quantile- Returns:
- F-1(u)
- See Also:
- Wikipedia: Quantile function
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mean
public double mean()
Description copied from interface:ProbabilityDistributionGets the mean of this distribution.- Specified by:
meanin interfaceProbabilityDistribution- Returns:
- the mean
- See Also:
- Wikipedia: Expected value
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moment
public double moment(double x)
Description copied from interface:ProbabilityDistributionThe moment generating function is the expected value of etX. That is,E(etX)
This may not always exist.- Specified by:
momentin interfaceProbabilityDistribution- Parameters:
x- t- Returns:
- E(exp(tX))
- See Also:
- Wikipedia: Moment-generating function
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skew
public double skew()
Description copied from interface:ProbabilityDistributionGets the skewness of this distribution.- Specified by:
skewin interfaceProbabilityDistribution- Returns:
- the skewness
- See Also:
- Wikipedia: Skewness
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variance
public double variance()
Description copied from interface:ProbabilityDistributionGets the variance of this distribution.- Specified by:
variancein interfaceProbabilityDistribution- Returns:
- the variance
- See Also:
- Wikipedia: Variance
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median
public double median()
Description copied from interface:ProbabilityDistributionGets the median of this distribution.- Specified by:
medianin interfaceProbabilityDistribution- Returns:
- the median
- See Also:
- Wikipedia: Median
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kurtosis
public double kurtosis()
Description copied from interface:ProbabilityDistributionGets the excess kurtosis of this distribution.- Specified by:
kurtosisin interfaceProbabilityDistribution- Returns:
- the excess kurtosis
- See Also:
- Wikipedia: Kurtosis
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entropy
public double entropy()
Description copied from interface:ProbabilityDistributionGets the entropy of this distribution.- Specified by:
entropyin interfaceProbabilityDistribution- Returns:
- the entropy
- See Also:
- Wikipedia: Entropy (information theory)
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