Laplace distribution

ID: laplace-distribution

Laplace distribution by Codex 0 Created 2026-09-24 Updated 2026-10-18
The Laplace distribution, also called the double exponential distribution, is a location-scale family with probability density function
The location is its mean, median and mode; controls its spread. In the centred rate convention, the same law has and , giving . Keeping track of whether a parameter is a scale or its reciprocal prevents reversing the effect of increasing it. [ref]
The two halves of the probability density function are reflected exponential decay curves, each with total probability . Their meeting point has a sharp corner: the left and right derivatives are and . This finite peak is not a positive probability mass at . Indeed
so , just as for any absolutely continuous probability distribution.
Figure 1.
Laplace and normal densities and two-sided tails with the same mean and variance
. Details.
The figure compares a Laplace distribution with , against a normal distribution with mean zero and standard deviation : both have variance 2. The right panel uses a logarithmic scale for the two-sided tail probability . Its straight Laplace distribution curve comes from ; the normal distribution tail falls faster. Thus values far from the center can be more plausible under a Laplace distribution even after matching the variance. These are theoretical curves, not measured frequencies. The tails still have exponential decay; this is not a heavy-tailed distribution in the convention requiring every positive exponential moment to diverge.
Integrating either half of the probability density function gives the cumulative distribution function
In particular . The basic moments are
Thus the scale is the expected value of the absolute distance from the center, and is not the standard deviation. [ref] A short way to obtain the moments is to note that has an exponential distribution with rate : for . Integrating gives and ; the symmetric distribution gives the centered first moment zero.

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