kernDeepStackNet: Kernel Deep Stacking Networks
Version 2.0.1

Contains functions for estimation and model selection of kernel deep stacking networks. The model selection includes direct optimization or model based alternatives with arbitrary loss functions.

AuthorThomas Welchowski <welchow@imbie.meb.uni-bonn.de> and Matthias Schmid <matthias.schmid@imbie.uni-bonn.de>
Date of publication2017-02-08 01:30:30
MaintainerThomas Welchowski <welchow@imbie.meb.uni-bonn.de>
LicenseGPL-3
Version2.0.1
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("kernDeepStackNet")

Getting started

Package overview

Popular man pages

calcTrA: Calculates the trace of the hat matrix
EImod: Expected improvement criterion replacement function
kernDeepStackNet-package: Kernel deep stacking networks with random Fourier...
mbo1d: Efficient global optimization with iterative point proposals
mboAll: Efficient global optimization inclusive meta model validation
rdcVarOrder: Variable ordering using randomized dependence coefficients...
tuneMboSharedCvKDSN: Tuning of KDSN with efficient global optimization given level...
See all...

All man pages Function index File listing

Man pages

calcTrA: Calculates the trace of the hat matrix
calcTrAFast: Calculates the trace of the hat matrix as C version
calcWdiag: Calculation of weight matrix
cancorRed: Calculate first canonical correlation
crossprodRcpp: Calculates the cross product of a matrix
devStandard: Predictive deviance of a linear model
EImod: Expected improvement criterion replacement function
fineTuneCvKDSN: Fine tuning of random weights of a given KDSN model
fitEnsembleKDSN: Fit an ensemble of KDSN
fitKDSN: Fit kernel deep stacking network with random Fourier...
fourierTransPredict: Prediction based on random Fourier transformation
gDerivMu: Derivative of the link function evaluated at the expected...
getEigenValuesRcpp: Calculates the eigenvalues of a matrix
kernDeepStackNet-package: Kernel deep stacking networks with random Fourier...
lossApprox: Kernel deep stacking network loss function
lossCvKDSN: Kernel deep stacking network loss function based on...
lossGCV: Generalized cross-validation loss
lossSharedCvKDSN: Kernel deep stacking network loss function based on...
lossSharedTestKDSN: Kernel deep stacking network loss function with test set and...
mbo1d: Efficient global optimization with iterative point proposals
mboAll: Efficient global optimization inclusive meta model validation
optimize1dMulti: One dimensional optimization of multivariate loss functions
predict.KDSN: Predict kernel deep stacking networks
predict.KDSNensemble: Predict kernel deep stacking networks ensembles
predict.KDSNensembleDisk: Predict kernel deep stacking networks ensembles
predLogProb: Predictive logarithmic probability of Kriging model
randomFourierTrans: Random Fourier transformation
rdcPart: Randomized dependence coefficient partial calculation
rdcSubset: Randomized dependence coefficients score on given subset
rdcVarOrder: Variable ordering using randomized dependence coefficients...
rdcVarSelSubset: Variable selection based on RDC with genetic algorithm
robustStandard: Robust standardization
tuneMboLevelCvKDSN: Tuning of KDSN with efficient global optimization given level...
tuneMboLevelGcvKDSN: Tuning of KDSN with efficient global optimization given level...
tuneMboSharedCvKDSN: Tuning of KDSN with efficient global optimization given level...
tuneMboSharedSubsetKDSN: Tuning subsets of KDSN with efficient global optimization and...
varMu: Variance function evaluated at expected value

Functions

Files

tests
tests/KDSNrcpp.R
tests/KDSNestimation_tests_robust_standard.R
tests/KDSNestimation_tests_fit_k_DSN_rft.R
tests/KDSNdirectOpt_tests_optimize_1D_multi_KDSN.R
tests/KDSNestimation_tests_randomFourierTrans.R
src
src/crossprodRcpp.cpp
src/eigenvalues.cpp
src/RcppExports.cpp
NAMESPACE
R
R/KDSNOptMisc.R
R/KDSNmodelBasedOpt.R
R/KDSNlossFunc.R
R/RcppExports.R
R/KDSNdirectOpt.R
R/KDSNvarSelect.R
R/KDSNestimation.R
MD5
DESCRIPTION
man
man/kernDeepStackNet-package.Rd
man/tuneMboLevelGcvKDSN.Rd
man/fitEnsembleKDSN.Rd
man/crossprodRcpp.Rd
man/gDerivMu.Rd
man/optimize1dMulti.Rd
man/mboAll.Rd
man/calcTrA.Rd
man/tuneMboSharedSubsetKDSN.Rd
man/fitKDSN.Rd
man/tuneMboLevelCvKDSN.Rd
man/rdcSubset.Rd
man/predLogProb.Rd
man/rdcPart.Rd
man/predict.KDSN.Rd
man/varMu.Rd
man/mbo1d.Rd
man/rdcVarOrder.Rd
man/rdcVarSelSubset.Rd
man/predict.KDSNensembleDisk.Rd
man/randomFourierTrans.Rd
man/devStandard.Rd
man/fineTuneCvKDSN.Rd
man/lossGCV.Rd
man/calcWdiag.Rd
man/lossSharedCvKDSN.Rd
man/fourierTransPredict.Rd
man/predict.KDSNensemble.Rd
man/EImod.Rd
man/calcTrAFast.Rd
man/cancorRed.Rd
man/robustStandard.Rd
man/lossSharedTestKDSN.Rd
man/lossCvKDSN.Rd
man/lossApprox.Rd
man/getEigenValuesRcpp.Rd
man/tuneMboSharedCvKDSN.Rd
kernDeepStackNet documentation built on May 19, 2017, 8:58 p.m.

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