Estimate credible interval from weighted samples.
cred(x, x0, w = NULL, cred.int = 0.95)
| x | Vector of random samples of variable. |
|---|---|
| x0 | Mean of median of variable. |
| w | Weight > 0 assigned to each sample. If w = NULL, all weights are the same. |
| cred.int | Credible interval must contain probability mass of at least this amount. A number between 0 and 1. |
Credible interval [a,b] is defined as smallest interval containing x0
that contains cred.int of the probability mass. Note that the credible
interval is not necessarily symmetric about x0. (Other definitions of the
credible interval are possible.)
The algorithm is quadratic in the length of x (and w), so should not be used for large numbers of samples.
list(a = a,b = b).
P. Carbonetto and M. Stephens (2012). Scalable variational inference for Bayesian variable selection in regression, and its accuracy in genetic association studies. Bayesian Analysis 7, 73--108.
x <- rnorm(100) out <- cred(x,mean(x),cred.int = 0.68)