SPOT: Sequential Parameter Optimization Toolbox
Version 2.0.1

A set of tools for model based optimization and tuning of algorithms. It includes surrogate models, optimizers and design of experiment approaches. The main interface is spot, which uses sequentially updated surrogate models for the purpose of efficient optimization. The main goal is to ease the burden of objective function evaluations, when a single evaluation requires a significant amount of resources.

AuthorThomas Bartz-Beielstein [aut], Joerg Stork [aut], Martin Zaefferer [aut, cre], Margarita Rebolledo [ctb], Christian Lasarczyk [ctb], Joerg Ziegenhirt [ctb], Wolfgang Konen [ctb], Oliver Flasch [ctb], Patrick Koch [ctb], Martina Friese [ctb]
Date of publication2017-03-08 16:37:21
MaintainerMartin Zaefferer <martin.zaefferer@gmx.de>
LicenseGPL (>= 2)
Version2.0.1
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("SPOT")

Getting started

Package overview

Popular man pages

buildEnsembleStack: Ensemble: Stacking
buildKrigingDACE: Build DACE model
corrcubic: Correlation: Cubic
corrgauss: Correlation: Gauss
corrspline: Correlation: Spline
evaluateModel: Evaluate Model
predict.spotSecondOrderModel: Prediction method for linear model
See all...

All man pages Function index File listing

Man pages

buildEnsembleStack: Ensemble: Stacking
buildKriging: Build Kriging Model
buildKrigingDACE: Build DACE model
buildLM: Linear Model Interface
buildRandomForest: Random Forest Interface
buildSO: Second Order Linear Model Interface
calculationBarthMuschelknautz: Cyclone Simulation: Barth/Muschelknautz
corrcubic: Correlation: Cubic
correxp: Correlation: Exp
correxpg: Correlation: Expg
corrgauss: Correlation: Gauss
corrkriging: Correlation: Kriging
corrlin: Correlation: Lin
corrnoisygauss: Correlation: Noisy Gauss
corrnoisykriging: Correlation: Noisy Kriging
corrspherical: Correlation: Spherical
corrspline: Correlation: Spline
daceEvalFit: Evaluate DACE fit
daceFixTheta: Fix model parameters DACE
daceGetFit: Get DACE fit
daceLikelihood: Wrapper for Maximum Likelihood Estimation
daceObjfunc: DACE objective function
dacePrepareFit: Prepare DACE fit
daceStartParameters: Start parameter setup DACE
dataGasSensor: Gas Sensor Data
designLHD: Latin Hypercube Design Generator
designLHDNorm: Normalized LHD Design
designUniformRandom: Uniform Design Generator
duplicateAndReplicateHandling: Handle Duplicates and Replicates
evaluateModel: Evaluate Model
expectedImprovement: Expected Improvement
funCyclone: Objective function - Cyclone Simulation: Barth/Muschelknautz
funSphere: Sphere Test Function
krigingLikelihood: Calculate negative log-likelihood
normalizeMatrix: Normalize design
normalizeMatrix2: Normalize design 2
objectiveFunctionEvaluation: Objective Function Evaluation
OCBA: Low Level OCBA
optimLBFGSB: Minimization by L-BFGS-B
optimLHD: Minimization by Latin Hypercube Sampling
predict.dace: DACE predictor
predict.ensembleStack: Predict Stacked Ensemble
predict.kriging: Predict Kriging Model
predictKrigingReinterpolation: Predict Kriging Model (Re-interpolating)
predict.spotLinearModel: Prediction method for linear model
predict.spotRandomForest: Prediction method for random forest
predict.spotSecondOrderModel: Prediction method for linear model
print: Print Function DACE Kriging
print.spotLinearModel: Print method for linear model
print.spotRandomForest: Print method for random forest
print.spotSecondOrderModel: Print method for linear model
regpoly0: Regression: Regpoly0
regpoly1: Regression: Regpoly1
regpoly2: Regression: Regpoly2
repairNonNumeric: Repair Non-numeric Values
repeatsOCBA: Optimal Computing Budget Allocation
repmat: repmat
spot: Sequential Parameter Optimization
spotHelpBslash: Backslash operator.
SPOT-package: Sequential Parameter Optimization Toolbox

Functions

Files

inst
inst/CITATION
tests
tests/testthat.R
tests/testthat
tests/testthat/test.main.R
tests/testthat/test.designLHD.R
tests/testthat/test.designUinformRandom.R
NAMESPACE
NEWS
data
data/dataGasSensor.RData
R
R/dataGasSensor.R
R/buildRandomForest.R
R/objectiveFunctionEvaluation.R
R/evaluate.R
R/buildLM.R
R/buildEnsembleStack.R
R/buildSO.R
R/duplicateHandling.R
R/designUniformRandom.R
R/optimLHD.R
R/repeatsOCBA.R
R/designLHD.R
R/buildKrigingForrester.R
R/sphere.R
R/optimLBFGSB.R
R/spot.R
R/buildKrigingDACE.R
R/package.R
R/repair.R
R/infill.R
R/cyclone.R
MD5
DESCRIPTION
man
man/daceStartParameters.Rd
man/predict.spotLinearModel.Rd
man/buildKrigingDACE.Rd
man/funCyclone.Rd
man/expectedImprovement.Rd
man/SPOT-package.Rd
man/objectiveFunctionEvaluation.Rd
man/buildEnsembleStack.Rd
man/calculationBarthMuschelknautz.Rd
man/spotHelpBslash.Rd
man/predict.kriging.Rd
man/corrnoisygauss.Rd
man/optimLBFGSB.Rd
man/designLHDNorm.Rd
man/repmat.Rd
man/corrkriging.Rd
man/normalizeMatrix2.Rd
man/evaluateModel.Rd
man/corrspherical.Rd
man/predict.dace.Rd
man/corrspline.Rd
man/daceObjfunc.Rd
man/optimLHD.Rd
man/predict.spotRandomForest.Rd
man/print.spotRandomForest.Rd
man/correxpg.Rd
man/predict.ensembleStack.Rd
man/corrcubic.Rd
man/correxp.Rd
man/designLHD.Rd
man/dacePrepareFit.Rd
man/repairNonNumeric.Rd
man/designUniformRandom.Rd
man/daceFixTheta.Rd
man/buildKriging.Rd
man/buildSO.Rd
man/normalizeMatrix.Rd
man/regpoly2.Rd
man/corrnoisykriging.Rd
man/dataGasSensor.Rd
man/repeatsOCBA.Rd
man/regpoly1.Rd
man/predictKrigingReinterpolation.Rd
man/daceGetFit.Rd
man/buildLM.Rd
man/daceLikelihood.Rd
man/daceEvalFit.Rd
man/predict.spotSecondOrderModel.Rd
man/print.spotLinearModel.Rd
man/spot.Rd
man/buildRandomForest.Rd
man/krigingLikelihood.Rd
man/corrgauss.Rd
man/print.spotSecondOrderModel.Rd
man/print.Rd
man/OCBA.Rd
man/funSphere.Rd
man/regpoly0.Rd
man/duplicateAndReplicateHandling.Rd
man/corrlin.Rd
.Rinstignore
SPOT documentation built on May 19, 2017, 11:14 a.m.

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