Package smile.stat.distribution
Class FDistribution
java.lang.Object
smile.stat.distribution.AbstractDistribution
smile.stat.distribution.FDistribution
- All Implemented Interfaces:
Serializable
,Distribution
F-distribution arises in the testing of whether two observed samples have
the same variance. A random variate of the F-distribution arises as the
ratio of two chi-squared variates.
- See Also:
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Field Summary
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Constructor Summary
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Method Summary
Modifier and TypeMethodDescriptiondouble
cdf
(double x) Cumulative distribution function.double
entropy()
Shannon entropy.int
length()
The number of parameters of the distribution.double
logp
(double x) The density at x in log scale, which may prevents the underflow problem.double
mean()
The mean of distribution.double
p
(double x) The probability density function for continuous distribution or probability mass function for discrete distribution at x.double
quantile
(double p) The quantile, the probability to the left of quantile is p.double
rand()
Generates a random number following this distribution.toString()
double
variance()
The variance of distribution.Methods inherited from class smile.stat.distribution.AbstractDistribution
inverseTransformSampling, quantile, quantile, rejection
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
Methods inherited from interface smile.stat.distribution.Distribution
likelihood, logLikelihood, rand, sd
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Field Details
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nu1
public final int nu1The degrees of freedom of chi-square distribution in numerator. -
nu2
public final int nu2The degrees of freedom chi-square distribution in denominator.
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Constructor Details
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FDistribution
public FDistribution(int nu1, int nu2) Constructor.- Parameters:
nu1
- the degree of freedom of chi-square distribution in numerator.nu2
- the degree of freedom of chi-square distribution in denominator.
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Method Details
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length
public int length()Description copied from interface:Distribution
The number of parameters of the distribution. The "length" is in the sense of the minimum description length principle.- Returns:
- The number of parameters.
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mean
public double mean()Description copied from interface:Distribution
The mean of distribution.- Returns:
- The mean.
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variance
public double variance()Description copied from interface:Distribution
The variance of distribution.- Returns:
- The variance.
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entropy
public double entropy()Shannon entropy. Not supported.- Returns:
- Shannon entropy.
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toString
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rand
public double rand()Description copied from interface:Distribution
Generates a random number following this distribution.- Returns:
- a random number.
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p
public double p(double x) Description copied from interface:Distribution
The probability density function for continuous distribution or probability mass function for discrete distribution at x.- Parameters:
x
- a real number.- Returns:
- the density.
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logp
public double logp(double x) Description copied from interface:Distribution
The density at x in log scale, which may prevents the underflow problem.- Parameters:
x
- a real number.- Returns:
- the log density.
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cdf
public double cdf(double x) Description copied from interface:Distribution
Cumulative distribution function. That is the probability to the left of x.- Parameters:
x
- a real number.- Returns:
- the probability.
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quantile
public double quantile(double p) Description copied from interface:Distribution
The quantile, the probability to the left of quantile is p. It is actually the inverse of cdf.- Parameters:
p
- the probability.- Returns:
- the quantile.
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