SPOT-package | Sequential Parameter Optimization Toolbox in R |
daceBuilder | Build DACE model |
dacePredictor | DACE predictor |
forrBuilder | Build Forrester Kriging |
forrCoBuilder | Build Forrester Co-Kriging |
forrCoRegPredictor | Predict Forrester Co-Kriging Model |
forrRegPredictor | Predict Forrester Model |
forrReintPredictor | Predict Forrester Model (Re-interpolating) |
predict.forr | Predict Forrester Model |
SPOT | Sequential Parameter Optimization Toolbox in R |
spot | Main function for the use of SPOT |
spotAlgEs | Evolution Strategy Implementation |
spotAlgStartEs | Interface for an Evolution Strategy to be tuned by SPOT... |
spotAlgStartEsGlg | Algorithm Interface to ES + GLG |
spotAlgStartEsVar | Interface for an Evolution Strategy to be robustly tuned by SPOT... |
spotAlgStartRgp | Interface for RGP to be tuned by SPOT |
spotAlgStartSann | Interface for SANN to be tuned by SPOT |
spotAlgStartSannVar | Interface for SANN to be tuned robustly by SPOT |
spotAlgStartSmsEmoaGlg | Algorithm Interface to ES + GLG |
spotBraninFunction | Single objective test functions for SPOT |
spotCreateDesignBasicDoe | spotCreateDesignBasicDoe |
spotCreateDesignFactors | spotCreateDesignFactors |
spotCreateDesignFrF2 | spotCreateDesignFrF2 |
spotCreateDesignLhd | spotCreateDesignLhd |
spotCreateDesignLhs | spotCreateDesignLhs |
spotCreateDesignLhsOpt | spotCreateDesignLhsOpt |
spotEnsembleMultiAlternate | spotEnsembleMultiAlternate |
spotEnsembleMultiAverage | spotEnsembleMultiAverage |
spotEnsembleMultiChoose | spotEnsembleMultiChoose |
spotEnsembleMultiRank | spotEnsembleMultiRank |
spotEnsembleMultiRankWeighted | spotEnsembleMultiRankWeighted |
spotEnsembleSingleBLAbern | Single Ensemble: BLAbern |
spotEnsembleSingleBLAnorm | Single Ensemble: BLAnorm |
spotEnsembleSingleEpsGreedy | Single Ensemble: Epsilon Greedy |
spotEnsembleSinglePOKER | Single Ensemble: POKER |
spotEnsembleSingleRoundSearch | Single Ensemble: RoundSearch |
spotEnsembleSingleSoftMax | Single Ensemble: SoftMax |
spotEnsembleSingleUCB1 | Single Ensemble: UCB1 |
spotFeedback | Ensemble Feedback Functions |
spotFeedback.deviation | Ensemble Feedback Functions |
spotFeedback.error.combo | Ensemble Feedback Functions |
spotFeedback.error.full | Ensemble Feedback Functions |
spotFeedback.error.last | Ensemble Feedback Functions |
spotFeedback.error.order | Ensemble Feedback Functions |
spotFeedback.reward.bern | Ensemble Feedback Functions |
spotFeedback.reward.norm | Ensemble Feedback Functions |
spotFeedback.sd.interSubModelsFull | Ensemble Feedback Functions |
spotFeedback.y | Ensemble Feedback Functions |
spotGetOptions | Set all options by conf-file or by default |
spotGlgCreate | Create Gaussian Landscape |
spotGlgCreateN | Create Gaussian Landscape (multiple) |
spotGlgCreateRot | Create Gaussian Landscape (rotated) |
spotGlgCreateRotSearched | Create Gaussian Landscape (rotated) with random search |
spotGlgEval | Gaussian Landscape Evaluation |
spotGlgEvalN | Gaussian Landscape Evaluation (multiple) |
spotGlgEvalRot | Gaussian Landscape Evaluation (rotated) |
spotGlgInit | Initialize Gaussian Landscape |
spotGlgInitN | Initialize Gaussian Landscape (multiple) |
spotGui | Start the SPOT GUI |
spotInfillExpImp | Neg. Log. of Expected Improvement Infill Criterion |
spotInfillHyperVolume | MCO Infill Criterion |
spotInfillLcbHyperVolume | Hypervolume Lower Confidence Bound Infill Criterion |
spotInfillLcbMulti | Lower Confidence Bound Infill Criterion |
spotInfillLcbSingle | Single objective lower confidence bound |
spotInfillProbImp | Probability of Improvement Infill Criterion |
spotInfillSD | Neg. SD Infill Criterion |
spotInfillSExI2d | S-metric Expected Improvement SExI Infill Criterion |
spotMexicanHatFunction | Single objective test functions for SPOT |
spotModel.func | Model Prediction Interface spotMode.func creates a function which represents the chosen surrogate model (see 'method' parameter). The created function will yield values predicted at given new locations. |
spotModel.predict | Model Prediction Interface This function is used to interface the 'spotPredict*' (e.g.: 'spotPredictRandomForest') functions. It serves as a simple interface to predict new data with on a surrogate models. |
spotModel.train | Model Training Interface This function is used to interface the 'spotPredict*' (e.g.: 'spotPredictRandomForest') functions. It serves as a simple interface to train surrogate models, as need by the user. |
spotModelDescentLm | Steepest Descent on RSM (linear model) Optimizes an existing fit of a linear model created by the rsm function. Uses steepest descent method and adaptation of ROI alternatingly. |
spotModelOptim | Optimize predicted meta model Optimizes an existing fit of a model to get an optimal new design point. Executed after building the prediction model in the sequential SPOT step. |
spotModelParetoOptim | Multi criteria optimization of predicted surrogate models Uses by default the number of design points expected as population size for multi criteria optimization of the models build in the current sequential step. Executed after building the prediction models. |
spotOcba | Optimal Computing Budget Allocation OCBA for SPOT |
spotOptim | spotOptim: optim-like spot interface |
spotOptimEs | spotOptimEs: optim-like ES interface |
spotOptimInterface | Interface for Target Functions |
spotOptimizationInterface | spotOptimizationInterface |
spotOptimizationInterfaceMco | spotOptimizationInterfaceMco |
spotOptimLHS | spotOptimLHS |
spotPenalizeMissingValues | Penalize Missing Values |
spotPredictCoForrester | Meta Model Interface: Forrester's Co-Kriging |
spotPredictDace | Meta Model Interface: DACE Kriging |
spotPredictDice | Meta Model Interface: Dice Kriging |
spotPredictEarth | Meta Model Interface: Multivariate Adaptive Regression Spline |
spotPredictEsvm | Meta Model Interface: Support Vector Machine |
spotPredictForrester | Meta Model Interface: Forrester's Kriging |
spotPredictGausspr | Meta Model Interface: Gaussian Processes |
spotPredictKrig | Meta Model Interface: Fields Kriging |
spotPredictKsvm | Meta Model Interface: Support Vector Machine |
spotPredictLm | Meta Model Interface: Linear Model |
spotPredictLmFactor | Meta Model Interface: Linear model with factors for SPOT |
spotPredictMCO | Meta Model Interface: Multi Criteria Modelling |
spotPredictMlegp | Meta Model Interface: Maximum Likelihood Estimation for Gaussian Processes, Kriging |
spotPredictMLP | Meta Model Interface: Multi-layer Perceptron |
spotPredictNeuralnet | Meta Model Interface: Neural network |
spotPredictQrnn | Meta Model Interface: Quantile Regression Neural Network |
spotPredictRandomForest | Meta Model Interface: Random Forest A prediction model interface based on randomForest package, using a random forest for regression. Can be used both for single and multi objective SPOT. |
spotPredictRandomForestMlegp | Meta Model Interface: Random Forest combined with Mlegp A very simple ensemble which uses results from a Gaussian process model (mlegp) and a random forest. |
spotPredictTgp | Meta Model Interface: Treed Gaussian Processes |
spotPredictTree | Meta Model Interface: Tree A prediction model based on rpart, using a single tree model. |
spotRastriginFunction | Single objective test functions for SPOT |
spotReadBstFile | Read .bst File |
spotReadRoi | Spot Read ROI |
spotRepairMissingValues | Repair Missing Values |
spotRepairMissingValuesCoKriging | Repair Missing Values |
spotReport3d | 3d Plot of Meta Model - Report Function |
spotReportContour | Model Contour Plot - Report Function |
spotReportDefault | Default Report |
spotReportEarth | Earth Report |
spotReportMAMP | MAMP Model Report |
spotReportMetaDefault | Default Report for Meta Runs |
spotReportSAMP | SAMP Model Report |
spotReportSens | Sensitivity Report |
spotROI | Region Of Interest Constructor |
spotRosenbrockFunction | Single objective test functions for SPOT |
spotRosenbrockGradientFunction | Single objective test functions for SPOT |
spotSelectionAdjustedRsq | Model selection and error estimation |
spotSelectionAic | Model selection and error estimation |
spotSelectionCriteria | Model selection and error estimation |
spotSelectionMae | Model selection and error estimation |
spotSelectionMse | Model selection and error estimation |
spotSelectionRmse | Model selection and error estimation |
spotSelectionRsq | Model selection and error estimation |
spotSelectionSae | Model selection and error estimation |
spotSelectionScaledMse | Model selection and error estimation |
spotSelectionScaledRmse | Model selection and error estimation |
spotSelectionScaledSse | Model selection and error estimation |
spotSelectionSse | Model selection and error estimation |
spotSExI2d | S-metric Expected Improvement SExI Infill Criterion |
spotSixHumpFunction | Single objective test functions for SPOT |
spotSmsEmoa | SMS-EMOA: S-Metric-Selection Evolutionary Multi-objective Optimization Algorithm |
spotSmsEmoaKriging | SMS-EMOA: S-Metric-Selection Evolutionary Multi-objective Optimization Algorithm |
spotSphere1Function | Single objective test functions for SPOT |
spotSphereFunction | Single objective test functions for SPOT |
spotStepAutoOpt | SPOT Step Auto Opt |
spotStepInitial | SPOT Step: Initialize (First SPOT- Step) |
spotStepMetaOpt | SPOT Step Meta |
spotStepReport | SPOT Step Report |
spotStepRunAlg | SPOT Step Algorithm Call |
spotStepSequential | SPOT Step Sequential |
spotSurf3d | spotSurf3d |
spotSurfContour | spotSurfContour |
spotWildFunction | Single objective test functions for SPOT |
spotWriteAroi | Spot Write Aroi |
Testfunctions | Single objective test functions for SPOT |