SLik object (as produced by MSL) and samples its parameter space in (hopefully) clever ways, not yet well documented. rparam calls sample_volume to define points targeting the likelihood maximum and the bounds of confidence intervals, with n for these different targets dependent on the mean square error of prediction of likelihood at the maximum and at CI bounds.
rparam(object, n= 1, useEI = list(max=TRUE,profileCI=TRUE,rawCI=FALSE), useCI = TRUE, verbose = interactive(), tryn=30*n, level = 0.95, CIweight=Infusion.getOption("CIweight"))
sample_volume(object, n = 6, useEI, vertices=NULL, dlr = NULL, verbose = interactive(), fixed = NULL, tryn= 30*n)SLik object
max, profileCI and rawCI determine this for three types of focal points, respectively the MSL estimate, profile CI bounds, and full-dimensional bounds. When EI is used, n points with best EI are selected among tryn points randomlygenerated in some neighborhood of the focal point.
vertices. By default, these vertices are taken from object$fit$data.
useCI is TRUE but confidence intervals are not available from the object, such intervals are computed with coverage level.
Infusion.getOption("LRthreshold")
= , defining a one-dimensional constraint in parameter space.
Points will be sampled in the intersection of the volume defined by the object and of such constraint(s).
useEI argument.
SLik object are considered.
if (Infusion.getOption("example_maxtime")>10) {
data(densv)
summliksurf <- infer_surface(densv) ## infer a log-likelihood surface
sample_volume(summliksurf)
}
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