R: Multivariate Laplace Random Deviates

rmLaplace {L1pack} | R Documentation

## Multivariate Laplace Random Deviates

### Description

Random number generation from the multivariate Laplace distribution.

### Usage

    rmLaplace(n = 1, center = rep(0, nrow(Scatter)), Scatter = diag(length(center)))

### Arguments

`n` | the number of samples requested
`center` | a vector giving the locations of each variable
`Scatter` | a positive-definite dispersion matrix

### Details

The function `rmLaplace` is an interface to C routines, which make calls to subroutines from LAPACK. The matrix decomposition is internally done using the Cholesky decomposition. If `Scatter` is not non-negative definite then there will be a warning message.

### Value

If `n = 1` a vector of the same length as `center`, otherwise a matrix of `n` rows of random vectors.

### References

Gomez, E., Gomez-Villegas, M.A., and Marin, J.M. (1998). A multivariate generalization of the power exponential family of distributions. Communications in Statistics - Theory and Methods 27, 589-600.

Kotz, S., Kozubowski, T.J., and Podgorski, K. (2001). The Laplace Distributions and Generalizations. Birkhauser, Boston.

### Examples

    # dispersion parameters
    Scatter <- matrix(c(1,.5,.5,1), ncol = 2)
    Scatter

    # generate the sample
    y <- rmLaplace(n = 2000, Scatter = Scatter)

    # scatterplot of a random bivariate Laplace sample with center
    # vector zero and scale matrix 'Scatter'
    par(pty = "s")
    plot(y, xlab = "", ylab = "")
    title("bivariate Laplace sample", font.main = 1)

[Package L1pack version 0.40 Index]