R/tfromw.R

In stephenslab/EbayesThresh: Empirical Bayes Thresholding and Related Methods

tfromw <- function(w, s = 1, prior = "laplace", bayesfac = FALSE, a = 0.5) {
#
#  Given the vector of weights w and s (sd), find the threshold or
#   vector of thresholds corresponding to these weights, under the
#   specified prior.
#  If bayesfac=TRUE the Bayes factor thresholds are found, otherwise
#   the posterior median thresholds are found.
#  If the Laplace prior is used, a gives the value of the inverse scale
#   (i.e., rate) parameter
#
	pr <- substring(prior, 1, 1)
	if(bayesfac) {
		z <- 1/w - 2
		if(pr == "l"){ 
		  if(length(w)>=length(s)) {
		    zz <- z
		  } else { zz <- rep(z, length(s)) }
		  tt <- vecbinsolv(zz, beta.laplace, 0, 10, s = s, a = a)
		}
		if(pr == "c")
			tt <- vecbinsolv(z, beta.cauchy, 0, 10)
	}
	else {
	  z <- 0
		if(pr == "l"){
		  zz <- rep(0, max(length(s), length(w)))
                  
		  # When x/s-s*a>25, laplace.threshzero has value
		  #  close to 1/2; The boundary value of x can be
		  #  treated as the upper bound for search.
  		  tt <- vecbinsolv(zz, laplace.threshzero, 0, s*(25+s*a),
                                   s = s, w = w, a = a)
		}
		if(pr == "c")
			tt <- vecbinsolv(z, cauchy.threshzero, 0, 10, w = w)
	}
	return(tt)
}