Nothing
provideCovFnParams <- function(gcvKgpointls,
gcvnuniquerows,
fittedNames=blackbox.getOption("fittedNames"),
ycolname=blackbox.getOption("ycolname"),
minSmoothness=blackbox.getOption("minSmoothness"),
miscOptions=blackbox.getOption("miscOptions"),
initCovFnParam=NULL,
cleanResu=NULL,
verbosity=blackbox.getOption("verbosity"),
optimizers=blackbox.getOption("optimizers")
) {
hglmLambdaEst <- hglmPhiEst <- lambdaEst <- NA
if ("optimizeKriging" %innc% miscOptions) {
Cfit <- CKrigcoefs(gcvKgpointls[, c(fittedNames, ycolname)], initCovFnParam=initCovFnParam,
covfnparamA=blackbox.getOption("CovFnParam"),
nuniquerows=gcvnuniquerows,optimizers=optimizers,verbosity=verbosity)
CovFnParam <- Cfit$covfnparam ##includes smoothness (FR->FR 09/2015: !! c'est le comportement de CKrigcoefs seulement quand option(minSmoothness) n'est pas nul...!!)
if("HGLM" %innc% miscOptions) {
hglmLambdaEst <- Cfit$hglmLambda
hglmPhiEst <- Cfit$hglmPhi
} else {
lambdaEst <- Cfit$lambda
}
if (verbosity) {
lllocalst <- paste("Estimation of covariance parameters required ", Cfit$fnEvalCount, " CV function evaluations")
cat(lllocalst, "\n")
lllocalst <- NA
}
names(CovFnParam) <- c(fittedNames, "smoothness") ##global
if (blackbox.getOption("verbosity")) cat("Cross-validation estimates of correlation function parameters:", "\n")
if( !is.null(cleanResu) && CovFnParam["smoothness"]<3.95) { ## FR->FR remplacer tous les tests null cleanResu par des tests class file...?
if (minSmoothness>1.99) { ## ie if we expect high smoothness
message.redef("(!!!) Estimated smoothness parameter <3.95: likelihood prediction may be very poor")
write("(!) Estimated smoothness parameter <3.95: likelihood prediction may be very poor", file=cleanResu)
}
} ## FR->FR le mettre dans returnCode ?
} else if (!(blackbox.getOption("CovFnParamInSettingsBool"))){ ## smoothness fixed in settings but covariance params not fixed in settings
## if we're here, then ( ! optimizeKriging) ... probably obsolete...
cat("Correlation function parameters set by rough heuristics", "\n")
CovFnParam <- ((blackbox.getOption("FONKgUp")-blackbox.getOption("FONKgLow"))[fittedNames])/blackbox.getOption("metarange")
CovFnParam <- c(CovFnParam, unlist(list(smoothness=minSmoothness)))
} else { ## everything is in settings
cat("Correlation function parameters set by user:", "\n")
CovFnParam <- c(blackbox.getOption("CovFnParam"), unlist(list(smoothness=minSmoothness)))
}
names(CovFnParam) <- c(fittedNames, "smoothness")
locNvalues <- CovFnParam
userNames <- sapply(fittedNames, formatName, format="ASCII")
names(locNvalues) <- c(userNames, "smoothness") ##global
if (blackbox.getOption("verbosity")) {
print(locNvalues)
cat("\n")
}
nuggetNA <- ( (("HGLM" %innc% miscOptions) && is.na(hglmLambdaEst))
|| ( ( ! ("HGLM" %innc% miscOptions)) && is.na(lambdaEst)))
if (nuggetNA) {
## CovFnParam In Settings => CKrigcoefs has not yet been run and lambda is still NA
Cfit <- CKrigcoefs(gcvKgpointls[, c(fittedNames, ycolname)],
nuniquerows=gcvnuniquerows,
covfnparamA=CovFnParam,
lambdaA=NA,
optimizers=optimizers)
if ("HGLM" %innc% miscOptions) {
hglmLambdaEst <- Cfit$hglmLambda
hglmPhiEst <- Cfit$hglmPhi
} else {
lambdaEst <- Cfit$lambda
}
}
return(list(CovFnParam=CovFnParam, lambdaEst=lambdaEst,method=Cfit$method))
}
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