data.eval: Murray...

In mpoll/scale: The Scaleable Langevin Exact Algorithm -- Reference Implementation

Usage

data.eval(beta.pos, data.idxs, factor = 1)

Arguments

beta.pos
data.idxs
factor

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (beta.pos, data.idxs, factor = 1) 
{
    grad.log.pi <- lap.log.pi <- numeric(dimen)
    for (i in 1:length(data.idxs)) {
        datum.call <- datum.eval(beta.pos, data.idxs[i])
        grad.log.pi <- grad.log.pi + datum.call$grad.log.pi
        lap.log.pi <- lap.log.pi + datum.call$lap.log.pi
    }
    list(grad.log.pi = factor * grad.log.pi, lap.log.pi = factor * 
        lap.log.pi)
  }

mpoll/scale documentation built on Dec. 9, 2019, 7:15 a.m.