Compute normalized probabilities from unnormalized log-probabilities.

normalizelogweights(logw)

## Arguments

logw Vector of unnormalized log-probabilities.

## Details

Guards against underflow or overflow by adjusting the log-probabilities so that the largest probability is 1.

## Value

Normalized probabilities such that the sum is equal to 1.

## 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.

## Examples

  logw <- rnorm(6)
w    <- normalizelogweights(logw)