Compute Monte Carlo estimates of credible intervals for coefficients in the fitted variable selection model. This function is used by summary.varbvs to generate credible intervals for coefficients of top-ranked variables.

varbvscoefcred (fit, vars, cred.int = 0.95, nr = 1000)

## Arguments

fit Output of function varbvs. Vector of indices or names of variables. If not specified, credible intervals are computed for all variables. Size of credible interval (number between 0 and 1). Number of Monte Carlo samples to draw to estimate credible intervals. Amore accurate estimate of the credible interval can be obtained by setting nr to a larger number, at the cost of increased computation time.

## Details

Here, the credible interval [a,b] is simply defined as a = quantile(x,0.5 - cred.int/2) and b = quantile(x,0.5 + cred.int/2), in which x is a vector of samples drawn from the posterior distribution.

## Value

a

Credible interval lower bounds.

b

Credible interval upper bounds.

## References

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.

varbvs, summary.varbvs