Class TriangularDistribution
- java.lang.Object
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- dev.nm.stat.distribution.univariate.TriangularDistribution
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- All Implemented Interfaces:
ProbabilityDistribution
public class TriangularDistribution extends Object implements ProbabilityDistribution
The triangular distribution is a continuous probability distribution with lower limit a, upper limit b and mode c, where a < b and a ≤ c ≤ b. The R equivalent functions aredtriangle, ptriangle, qtriangle, rtriangle
in package 'triangle'.- See Also:
- Wikipedia: Triangular distribution
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Constructor Summary
Constructors Constructor Description TriangularDistribution(double min, double mode, double max)
Constructs an instance of a Triangular distribution.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description double
cdf(double x)
Gets the cumulative probability F(x) = Pr(X ≤ x).double
density(double x)
The density function, which, if exists, is the derivative of F.double
entropy()
Gets the entropy of this distribution.double
kurtosis()
Gets the excess kurtosis of this distribution.double
mean()
Gets the mean of this distribution.double
median()
Gets the median of this distribution.double
moment(double t)
The moment generating function is the expected value of etX.double
quantile(double u)
Gets the quantile, the inverse of the cumulative distribution function.double
skew()
Gets the skewness of this distribution.double
variance()
Gets the variance of this distribution.
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Method Detail
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mean
public double mean()
Description copied from interface:ProbabilityDistribution
Gets the mean of this distribution.- Specified by:
mean
in interfaceProbabilityDistribution
- Returns:
- the mean
- See Also:
- Wikipedia: Expected value
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median
public double median()
Description copied from interface:ProbabilityDistribution
Gets the median of this distribution.- Specified by:
median
in interfaceProbabilityDistribution
- Returns:
- the median
- See Also:
- Wikipedia: Median
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variance
public double variance()
Description copied from interface:ProbabilityDistribution
Gets the variance of this distribution.- Specified by:
variance
in interfaceProbabilityDistribution
- Returns:
- the variance
- See Also:
- Wikipedia: Variance
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skew
public double skew()
Description copied from interface:ProbabilityDistribution
Gets the skewness of this distribution.- Specified by:
skew
in interfaceProbabilityDistribution
- Returns:
- the skewness
- See Also:
- Wikipedia: Skewness
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kurtosis
public double kurtosis()
Description copied from interface:ProbabilityDistribution
Gets the excess kurtosis of this distribution.- Specified by:
kurtosis
in interfaceProbabilityDistribution
- Returns:
- the excess kurtosis
- See Also:
- Wikipedia: Kurtosis
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entropy
public double entropy()
Description copied from interface:ProbabilityDistribution
Gets the entropy of this distribution.- Specified by:
entropy
in interfaceProbabilityDistribution
- Returns:
- the entropy
- See Also:
- Wikipedia: Entropy (information theory)
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cdf
public double cdf(double x)
Description copied from interface:ProbabilityDistribution
Gets the cumulative probability F(x) = Pr(X ≤ x).- Specified by:
cdf
in interfaceProbabilityDistribution
- Parameters:
x
- x- Returns:
- F(x) = Pr(X ≤ x)
- See Also:
- Wikipedia: Cumulative distribution function
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density
public double density(double x)
Description copied from interface:ProbabilityDistribution
The 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:
density
in interfaceProbabilityDistribution
- Parameters:
x
- x- Returns:
- f(x)
- See Also:
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quantile
public double quantile(double u)
Description copied from interface:ProbabilityDistribution
Gets 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:
quantile
in interfaceProbabilityDistribution
- Parameters:
u
-u
, a quantile- Returns:
- F-1(u)
- See Also:
- Wikipedia: Quantile function
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moment
public double moment(double t)
Description copied from interface:ProbabilityDistribution
The moment generating function is the expected value of etX. That is,E(etX)
This may not always exist.- Specified by:
moment
in interfaceProbabilityDistribution
- Parameters:
t
- t- Returns:
- E(exp(tX))
- See Also:
- Wikipedia: Moment-generating function
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