rparam {Infusion} | R Documentation |
Sample the parameter space
Description
These functions take an 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.
Usage
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)
Arguments
object |
an |
n |
The number of parameter points to be produced |
useEI |
List of booleans, each determining whether to use an “expected improvement” (EI) criterion (e.g. Bingham et al., 2014) to select candidate parameter points to better ascertain a particular focal point. The elements |
vertices |
Points are sampled within a convex hull defined by |
useCI |
Whether to define points targeting the bounds of confidence intervals for the parameters. An expected improvement criterion is also used here. |
level |
If |
dlr |
A (log)likelihood ratio threshold used to select points in the upper region of the likelihood surface. Default value is
given by |
verbose |
Whether to display some information about selection of points, or not |
fixed |
A list or named vector, of which each element is of the form |
tryn |
See |
CIweight |
For development purposes, not documented. |
Value
a data frame of parameter points. Only parameters variable in the SLik
object are considered.
References
D. Bingham, P. Ranjan, and W.J. Welch (2014) Design of Computer Experiments for Optimization, Estimation of Function Contours, and Related Objectives, pp. 109-124 in Statistics in Action: A Canadian Outlook (J.F. Lawless, ed.). Chapman and Hall/CRC.
Examples
if (Infusion.getOption("example_maxtime")>10) {
data(densv)
summliksurf <- infer_surface(densv) ## infer a log-likelihood surface
sample_volume(summliksurf)
}