shrink_knots

%==nc%

%innc%

%w/o%

AUEformat

CcovFocal

GCV_lamVar_covFix_Wrapper

Krig_coef_Wrapper

R_GCV_lamVar_covFix

getFnEvalCount

newCSmooth

flushCSmoothTable

calcKnotsInfo

profileByFullHull

calcGridRelProfile

calcBounds1D

generateNextpointsfromCI

toCanonical

bbrhull

CKrigcoefs

Cpredict

Hreprrational

OKrig

LRTfn

LowUpFromKnots

LowUpfn

addSimplexEq

addtoedges

as.surface

bounds1D

calcKnotsInfoWrapper

canonize

checklogicalbounds

condaxialS2fromg

constrOptimR

constrSymOrRefl

constrSymOrReflWrapper

deleteCSmooth

euclidian

calcGridFromxy

findReplicates

findglobalMLE

fitinbounds

formatName

from2Ns2Tocanon

fromFONKtoanyspace

fromCanonToFONK

generateInitpts

generateNewPoints

generatePredictor

get_os

greedyMAXMINwithFixed

gridfn

groot

handlesPointAtEdge

insert.at

isPointInCHull

isoline

knotsFromLRTlist

knotsFromProfileEdges

.ls.objects

lsos

lsOK

make.surface.grid

makeplot

makeplottypes

maketicks

mantissExp

massBarycenter

matchVertCons

message.redef

messageNAMED

minimiseGCV

myprettyW

optimWrapper

overcat

overmessage

parse.grid.list

plot.OKrig

plot.OKriglistplus

plotParPoints

plot1DprofFrom2D

plotSlice

pointsToFONK

predict.OKrig

predict.OKriglistplus

predict_surface

prettyNamedUserValues

prettyPlotMain

prettyUserValues

prettynum

print.OKrig

print.OKriglistplus

print.bboptim

summary.bboptim

summary.OKriglistplus

profileBySubHull

provideCovFnParams

provideDevice

internal

ordinary-internal

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.

ordinary-internal: Internal ordinary Functions

Description

Arguments

Details