LogNormalDistribution

java.lang.Object
- smile.stat.distribution.AbstractDistribution
- - smile.stat.distribution.LogNormalDistribution

All Implemented Interfaces:

java.io.Serializable, Distribution
```
public class LogNormalDistribution
extends AbstractDistribution
```
A log-normal distribution is a probability distribution of a random variable whose logarithm is normally distributed. The log-normal distribution is the single-tailed probability distribution of any random variable whose logarithm is normally distributed. If X is a random variable with a normal distribution, then Y = exp(X) has a log-normal distribution; likewise, if Y is log-normally distributed, then log(Y) is normally distributed. A variable might be modeled as log-normal if it can be thought of as the multiplicative product of many independent random variables each of which is positive.

See Also:

Serialized Form

Field Summary

Fields
Modifier and Type Field and Description

double mu
The mean of normal distribution.

double sigma
The standard deviation of normal distribution.

Fields
Modifier and Type	Field and Description
`double`	`mu` The mean of normal distribution.
`double`	`sigma` The standard deviation of normal distribution.

Constructor Summary

Constructors
Constructor and Description

LogNormalDistribution(double mu, double sigma)
Constructor.

Constructors
Constructor and Description
`LogNormalDistribution(double mu, double sigma)` Constructor.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`double`	`cdf(double x)` Cumulative distribution function.
`double`	`entropy()` Shannon entropy of the distribution.
`static LogNormalDistribution`	`fit(double[] data)` Estimates the distribution parameters by MLE.
`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.
`java.lang.String`	`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

- Field Detail
  - mu
```
public final double mu
```
    The mean of normal distribution.
  - sigma
```
public final double sigma
```
    The standard deviation of normal distribution.
- Constructor Detail
  - LogNormalDistribution
```
public LogNormalDistribution(double mu,
                             double sigma)
```
    Constructor.
    
    Parameters:
    
    mu - the mean of normal distribution.
    
    sigma - the standard deviation of normal distribution.
- Method Detail
  - fit
```
public static LogNormalDistribution fit(double[] data)
```
    Estimates the distribution parameters by MLE.
  - 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.
  - mean
```
public double mean()
```
    Description copied from interface: Distribution
    
    The mean of distribution.
  - variance
```
public double variance()
```
    Description copied from interface: Distribution
    
    The variance of distribution.
  - entropy
```
public double entropy()
```
    Description copied from interface: Distribution
    
    Shannon entropy of the distribution.
  - toString
```
public java.lang.String toString()
```
    Overrides:
    
    toString in class java.lang.Object
  - rand
```
public double rand()
```
    Description copied from interface: Distribution
    
    Generates a random number following this distribution.
  - 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.
  - logp
```
public double logp(double x)
```
    Description copied from interface: Distribution
    
    The density at x in log scale, which may prevents the underflow problem.
  - cdf
```
public double cdf(double x)
```
    Description copied from interface: Distribution
    
    Cumulative distribution function. That is the probability to the left of x.
  - 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.

Class LogNormalDistribution

Field Summary

Constructor Summary

Method Summary

Methods inherited from class smile.stat.distribution.AbstractDistribution

Methods inherited from class java.lang.Object

Methods inherited from interface smile.stat.distribution.Distribution

Field Detail

mu

sigma

Constructor Detail

LogNormalDistribution

Method Detail

fit

length

mean

variance

entropy

toString

rand

p

logp

cdf

quantile