| DiscreteLaplace {extraDistr} | R Documentation | 
Discrete Laplace distribution
Description
Probability mass, distribution function and random generation for the discrete Laplace distribution parametrized by location and scale.
Usage
ddlaplace(x, location, scale, log = FALSE)
pdlaplace(q, location, scale, lower.tail = TRUE, log.p = FALSE)
rdlaplace(n, location, scale)
Arguments
x, q | 
 vector of quantiles.  | 
location | 
 location parameter.  | 
scale | 
 scale parameter;   | 
log, log.p | 
 logical; if TRUE, probabilities p are given as log(p).  | 
lower.tail | 
 logical; if TRUE (default), probabilities are   | 
n | 
 number of observations. If   | 
Details
If U \sim \mathrm{Geometric}(1-p) and
V \sim \mathrm{Geometric}(1-p),
then U-V \sim \mathrm{DiscreteLaplace}(p),
where geometric distribution is related to discrete Laplace distribution
in similar way as exponential distribution is related to Laplace distribution.
Probability mass function
f(x) = \frac{1-p}{1+p} p^{|x-\mu|}
Cumulative distribution function
F(x) = \left\{\begin{array}{ll}
\frac{p^{-|x-\mu|}}{1+p} & x < 0 \\
1 - \frac{p^{|x-\mu|+1}}{1+p} & x \ge 0
\end{array}\right.
References
Inusah, S., & Kozubowski, T.J. (2006). A discrete analogue of the Laplace distribution. Journal of statistical planning and inference, 136(3), 1090-1102.
Kotz, S., Kozubowski, T., & Podgorski, K. (2012). The Laplace distribution and generalizations: a revisit with applications to communications, economics, engineering, and finance. Springer Science & Business Media.
Examples
p <- 0.45
x <- rdlaplace(1e5, 0, p)
xx <- seq(-200, 200, by = 1)
plot(prop.table(table(x)))
lines(xx, ddlaplace(xx, 0, p), col = "red")
hist(pdlaplace(x, 0, p))
plot(ecdf(x))
lines(xx, pdlaplace(xx, 0, p), col = "red", type = "s")