quantile.lgcpPredict: quantile.lgcpPredict function

In bentaylor1/lgcp: Log-Gaussian Cox Process

Description

This function requires data to have been dumped to disk: see ?dump2dir and ?setoutput. The routine quantile.lgcpPredict computes quantiles of functions of Y. For example, to get cell-wise quantiles of exceedance probabilities, set fun=exp. Since computign the quantiles is an expensive operation, the option to output the quantiles on a subregion of interest is also provided (by setting the argument inWindow, which has a sensible default).

Usage

## S3 method for class 'lgcpPredict'
quantile(x, qt, tidx = NULL, fun = NULL,
  inWindow = x$xyt$window, crop2parentwindow = TRUE, startidx = 1,
  sampcount = NULL, ...)

Arguments

x	an object of class lgcpPredict
qt	a vector of the required quantiles
tidx	the index number of the the time interval of interest, default is the last time point.
fun	a 1-1 function (default the identity function) to be applied cell-wise to the grid. Must be able to evaluate sapply(vec,fun) for vectors vec.
inWindow	an observation owin window on which to compute the quantiles, can speed up calculation. Default is x$xyt$window.
crop2parentwindow	logical: whether to only compute the quantiles for cells inside x$xyt$window (the 'parent window')
startidx	optional starting sample index for computing quantiles. Default is 1.
sampcount	number of samples to include in computation of quantiles after startidx. Default is all
...	additional arguments

Value

an array, the [,,i]th slice being the grid of cell-wise quantiles, qt[i], of fun(Y), where Y is the MCMC output dumped to disk.

See Also

lgcpPredict, dump2dir, setoutput, plot.lgcpQuantiles

bentaylor1/lgcp documentation built on May 12, 2019, 2:09 p.m.