# Function beta for the Laplace prior

### Description

Given a value or vector *x* of values, find the value(s) of the function
*beta(x) = g(x)/phi(x) - 1 *,
where *g* is the convolution of the Laplace density with scale parameter *a* with with the normal density *phi(x)*.

### Usage

1 | ```
beta.laplace(x, a = 0.5)
``` |

### Arguments

`x` |
the value or vector of data values |

`a` |
the scale parameter of the Laplace distribution |

### Value

A vector the same length as *x* is returned, containing the value(s) *beta(x)*.

### Note

The Laplace density is given by
*gamma(u)= (a/2) exp ( - a|u| ) *
and is also known as the double exponential density.

### Author(s)

Bernard Silverman

### References

See `ebayesthresh`

and http://www.bernardsilverman.com

### See Also

`beta.cauchy`

### Examples

1 2 | ```
beta.laplace(c(-2,1,0,-4,8,50))
beta.laplace(c(-2,1,0,-4,8,50), a=1)
``` |

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker. Vote for new features on Trello.