postmed {ebayesthresh}R Documentation

Posterior median estimator

Description

Given a data value or a vector of data, find the corresponding posterior median estimate(s) of the underlying signal value(s)

Usage

postmed(x, w, prior = "laplace", a = 0.5)

Arguments

x a data value or a vector of data
w the value of the prior probability that the signal is nonzero
prior family of the nonzero part of the prior; can be "cauchy" or "laplace"
a the scale parameter of the nonzero part of the prior if the Laplace prior is used

Value

If x is a scalar, the posterior median med(theta|x) where theta is the mean of the distribution from which x is drawn. If x is a vector with elements x_1, ... , x_n, then the vector returned has elements med(theta_i|x_i), where each x_i has mean theta_i, all with the given prior.

Note

If the quasicauchy prior is used, the argument a is ignored. The routine calls the approprate one of postmed.laplace or postmed.cauchy.

Author(s)

Bernard Silverman

References

See ebayesthresh and http://www.bernardsilverman.com

See Also

postmed.laplace, postmed.cauchy, postmean

Examples

postmed(c(-2,1,0,-4,8,50), w=0.05, prior="cauchy")
postmed(c(-2,1,0,-4,8,50), w=0.2, prior="laplace", a=0.3)

[Package Contents]