Package smile.stat.distribution
Class LogisticDistribution
java.lang.Object
smile.stat.distribution.LogisticDistribution
- All Implemented Interfaces:
Serializable
,Distribution
The logistic distribution is a continuous probability distribution whose
cumulative distribution function is the logistic function, which appears
in logistic regression and feedforward neural networks. It resembles
the normal distribution in shape but has heavier tails (higher kurtosis).
The logistic distribution and the S-shaped pattern that results from it have been extensively used in many different areas such as:
- Biology - to describe how species populations grow in competition.
- Epidemiology - to describe the spreading of epidemics.
- Psychology - to describe learning.
- Technology - to describe how new technologies diffuse and substitute for each other.
- Market - the diffusion of new-product sales.
- Energy - the diffusion and substitution of primary energy sources.
- 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()
Returns Shannon entropy of the distribution.int
length()
Returns 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()
Returns 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.double
sd()
Returns the standard deviation of distribution.toString()
double
variance()
Returns the variance of distribution.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
inverseTransformSampling, likelihood, logLikelihood, quantile, quantile, rand, rejectionSampling
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Field Details
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mu
public final double muThe location parameter. -
scale
public final double scaleThe scale parameter.
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Constructor Details
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LogisticDistribution
public LogisticDistribution(double mu, double scale) Constructor.- Parameters:
mu
- the location parameter.scale
- the scale parameter.
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Method Details
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length
public int length()Description copied from interface:Distribution
Returns the number of parameters of the distribution. The "length" is in the sense of the minimum description length principle.- Specified by:
length
in interfaceDistribution
- Returns:
- The number of parameters.
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mean
public double mean()Description copied from interface:Distribution
Returns the mean of distribution.- Specified by:
mean
in interfaceDistribution
- Returns:
- The mean.
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variance
public double variance()Description copied from interface:Distribution
Returns the variance of distribution.- Specified by:
variance
in interfaceDistribution
- Returns:
- The variance.
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sd
public double sd()Description copied from interface:Distribution
Returns the standard deviation of distribution.- Specified by:
sd
in interfaceDistribution
- Returns:
- The standard deviation.
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entropy
public double entropy()Description copied from interface:Distribution
Returns Shannon entropy of the distribution.- Specified by:
entropy
in interfaceDistribution
- 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.- Specified by:
rand
in interfaceDistribution
- 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.- Specified by:
p
in interfaceDistribution
- 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.- Specified by:
logp
in interfaceDistribution
- 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.- Specified by:
cdf
in interfaceDistribution
- 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.- Specified by:
quantile
in interfaceDistribution
- Parameters:
p
- the probability.- Returns:
- the quantile.
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