calcPredictorOK

Input data frame as produced by <code><a href="/link/buildFONKgpointls?package=blackbox&version=1.0" rd-options="" data-mini-rdoc="blackbox::buildFONKgpointls">buildFONKgpointls</a></code>

FONKgpointls

NULL or numeric. At least this many rows (if available) should be selected for Kriging. The default value depends on the number p of predictor variables and is
  90, 159,  500, 1307, 3050, 6560 for p from 1 to 6 (beyond which it is strongly advised to us

minKrigPtNbr

NULL or Numeric. For large data sets the selected points are not <dquote>Kriged</dquote> all together. Rather, overlapping blocks of rows are selected and are Kriged separately. This sets the size of the blocks. Default depends on the operating system (se

krigmax

Controls the way rows are selected. For development purposes, should not be modified

topmode

Boolean. Whether to plot one-dimensional <dquote>profiles</dquote> of the raw data.

rawPlots

A connection, or a character string naming a file for some nicely formated output. If <code>""</code> (the default), print to the standard output connection.

cleanResu

Assuming that <code><a href="/link/calcGCV?package=blackbox&version=1.0" rd-options="" data-mini-rdoc="blackbox::calcGCV">calcGCV</a></code> has been first run to estimate smoothing parameter, this produces a <dquote>Kriging</dquote> predictor of the response.

Performs prediction of a response function from simulated response values, allowing black-box optimization of functions estimated with some error. blackbox includes a simple user interface for such applications, as well as more specialized functions designed to be called by the Migraine software (see URL). The latter functions are used for prediction of likelihood surfaces and implied likelihood ratio confidence intervals, and for exploration of predictor space of the surface. Prediction of the response is based on ordinary kriging (with residual error) of the input. Estimation of smoothing parameters is performed by generalized cross validation.

calcPredictorOK: Generate smoothing predictor given smoothing parameters

Description

Usage

Arguments

Value