Compute normalized probabilities from unnormalized log-probabilities.
Vector of unnormalized log-probabilities.
Guards against underflow or overflow by adjusting the log-probabilities so that the largest probability is 1.
Normalized probabilities such that the sum is equal to 1.
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.
logw <- rnorm(6) w <- normalizelogweights(logw)