Log-Laplace distribution

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Log-Laplace distribution
Probability density function
Probability density functions for Log-Laplace distributions with varying parameters μ and b.
Cumulative distribution function
Cumulative distribution functions for Log-Laplace distributions with varying parameters μ and b.

In probability theory and statistics, the log-Laplace distribution is the probability distribution of a random variable whose logarithm has a Laplace distribution. If X has a Laplace distribution with parameters μ and b, then Y = eX has a log-Laplace distribution. The distributional properties can be derived from the Laplace distribution.

Characterization

A random variable has a log-Laplace(μ, b) distribution if its probability density function is:[1]

f(x|μ,b)=12bxexp(|lnxμ|b)

The cumulative distribution function for Y when y > 0, is

F(y)=0.5[1+sgn(ln(y)μ)(1exp(|ln(y)μ|/b))].

Generalization

Versions of the log-Laplace distribution based on an asymmetric Laplace distribution also exist.[2] Depending on the parameters, including asymmetry, the log-Laplace may or may not have a finite mean and a finite variance.[2]

References

  1. Lindsey, J.K. (2004). Statistical analysis of stochastic processes in time. Cambridge University Press. p. 33. ISBN 978-0-521-83741-5. 
  2. 2.0 2.1 "A Log-Laplace Growth Rate Model". University of Nevada-Reno. p. 4. http://wolfweb.unr.edu/homepage/tkozubow/0_logs.pdf.