tfromw {EbayesThresh} | R Documentation |
Given a weight or vector of weights (i.e. prior probabilities that the parameter is nonzero), find the corresponding threshold(s) under the specified prior.
tfromw(w, prior = "laplace", bayesfac = FALSE, a = 0.5)
w |
prior weight or vector of weights |
prior |
specification of prior to be used; can be "cauchy" or "laplace" |
bayesfac |
specifies whether Bayes factor threshold should be used instead of posterior median threshold |
a |
scale factor if Laplace prior is used. Ignored if Cauchy prior is used. |
The Bayes factor method uses a threshold such that the posterior probability of zero is
exactly half if the data value is equal to the threshold.
If bayesfac
is set to FALSE (the default)
then the threshold is that of the posterior median function given the data value.
The routine carries out a binary search over each
component of an appropriate vector function, using the routine
vecbinsolv
.
For the posterior median threshold, the function to be zeroed is
laplace.threshzero
or cauchy.threshzero
.
For the Bayes factor threshold, the corresponding functions
are beta.laplace
or beta.cauchy
.
The value or vector of values of the estimated threshold(s).
Bernard Silverman
See ebayesthresh
and http://www.bernardsilverman.com
tfromw(c(0.05, 0.1)) tfromw(c(0.05, 0.1), prior="cauchy", bayesfac=TRUE)