Package index
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mlr3forecastmlr3forecast-package - mlr3forecast: Extending 'mlr3' to Time Series Forecasting
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LearnerFcst - Forecast Learner
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RecursiveForecaster - Recursive Forecast Learner
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DirectForecaster - Direct Multi-Step Forecast Learner
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mlr_learners_fcst.adamLearnerFcstAdam - ADAM Forecast Learner
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mlr_learners_fcst.arfimaLearnerFcstArfima - ARFIMA Forecast Learner
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mlr_learners_fcst.arimaLearnerFcstArima - ARIMA Forecast Learner
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mlr_learners_fcst.auto_adamLearnerFcstAutoAdam - Auto ADAM Forecast Learner
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mlr_learners_fcst.auto_arimaLearnerFcstAutoArima - Auto ARIMA Forecast Learner
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mlr_learners_fcst.auto_cesLearnerFcstAutoCes - Auto CES Forecast Learner
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mlr_learners_fcst.auto_gumLearnerFcstAutoGum - Auto GUM Forecast Learner
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mlr_learners_fcst.auto_msarimaLearnerFcstAutoMsarima - Auto Multiple-Seasonal ARIMA Forecast Learner
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mlr_learners_fcst.auto_ssarimaLearnerFcstAutoSsarima - Auto State-Space ARIMA Forecast Learner
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mlr_learners_fcst.baggedLearnerFcstBaggedModel - Bagged Model Forecast Learner
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mlr_learners_fcst.batsLearnerFcstBats - BATS Forecast Learner
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mlr_learners_fcst.cesLearnerFcstCes - CES Forecast Learner
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mlr_learners_fcst.crostonLearnerFcstCroston - Croston Forecast Learner
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mlr_learners_fcst.elmLearnerFcstElm - Extreme Learning Machine Forecast Learner
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mlr_learners_fcst.esLearnerFcstEs - Exponential Smoothing Forecast Learner
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mlr_learners_fcst.etsLearnerFcstEts - ETS Forecast Learner
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mlr_learners_fcst.gumLearnerFcstGum - GUM Forecast Learner
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mlr_learners_fcst.holt_wintersLearnerFcstHoltWinters - Holt-Winters Forecast Learner
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mlr_learners_fcst.meanLearnerFcstMean - Mean Forecast Learner
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mlr_learners_fcst.mlpLearnerFcstMlp - Multilayer Perceptron Forecast Learner
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mlr_learners_fcst.msarimaLearnerFcstMsarima - Multiple-Seasonal ARIMA Forecast Learner
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mlr_learners_fcst.nnetarLearnerFcstNnetar - Neural Network Forecast Learner
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mlr_learners_fcst.prophetLearnerFcstProphet - Prophet Forecast Learner
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mlr_learners_fcst.random_walkLearnerFcstRandomWalk - Random Walk Forecast Learner
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mlr_learners_fcst.rlgtLearnerFcstRlgt - Local and Global Trend Forecast Learner
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mlr_learners_fcst.smaLearnerFcstSma - Simple Moving Average Forecast Learner
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mlr_learners_fcst.splineLearnerFcstSpline - Spline Forecast Learner
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mlr_learners_fcst.ssarimaLearnerFcstSsarima - State-Space ARIMA Forecast Learner
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mlr_learners_fcst.stlmLearnerFcstStlm - STL + ETS/ARIMA Forecast Learner
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mlr_learners_fcst.struct_tsLearnerFcstStructTS - Structural Time Series Forecast Learner
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mlr_learners_fcst.tbatsLearnerFcstTbats - TBATS Forecast Learner
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mlr_learners_fcst.thetaLearnerFcstTheta - Theta Forecast Learner
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mlr_learners_fcst.tscountLearnerFcstTscount - Count Time Series Forecast Learner
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mlr_learners_fcst.tslmLearnerFcstTslm - Time Series Linear Model Forecast Learner
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TaskFcst - Forecast Task
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mlr_tasks_airpassengers - Air Passengers Forecast Task
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mlr_tasks_electricity - Daily electricity demand for Victoria, Australia Forecast Task
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mlr_tasks_livestock - Australian Livestock Slaughter Forecast Task
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mlr_tasks_lynx - Annual Canadian Lynx Trappings Forecast Task
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mlr_tasks_usaccdeaths - Accidental Deaths in the US Forecast Task
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mlr_measures_fcst.acf1MeasureACF1 - Autocorrelation at Lag 1
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mlr_measures_fcst.coverageMeasureCoverage - Empirical Coverage
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mlr_measures_fcst.maseMeasureMASE - Mean Absolute Scaled Error
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mlr_measures_fcst.mdaMeasureMDA - Mean Directional Accuracy
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mlr_measures_fcst.mdpvMeasureMDPV - Mean Directional Percentage Value
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mlr_measures_fcst.mdvMeasureMDV - Mean Directional Value
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mlr_measures_fcst.mpeMeasureMPE - Mean Percentage Error
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mlr_measures_fcst.msisMeasureMSIS - Mean Scaled Interval Score
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mlr_measures_fcst.pinballMeasurePinball - Pinball Loss
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mlr_measures_fcst.rmsseMeasureRMSSE - Root Mean Squared Scaled Error
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mlr_measures_fcst.wapeMeasureWAPE - Weighted Absolute Percentage Error
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mlr_measures_fcst.winklerMeasureWinkler - Winkler Score
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mlr_resamplings_fcst.cvResamplingFcstCV - Forecast Cross-Validation Resampling
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mlr_resamplings_fcst.holdoutResamplingFcstHoldout - Forecast Holdout Resampling
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mlr_pipeops_fcst.catch22PipeOpFcstCatch22 - Time Series Feature Extraction (catch22)
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mlr_pipeops_fcst.feastsPipeOpFcstFeasts - Time Series Feature Extraction (feasts)
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mlr_pipeops_fcst.fourierPipeOpFcstFourier - Create Fourier Features for Seasonality
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mlr_pipeops_fcst.lagsPipeOpFcstLags - Create Lags of Target Variable
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mlr_pipeops_fcst.rollingPipeOpFcstRolling - Create Rolling Window Features of Target Variable
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mlr_pipeops_fcst.targetboxcoxPipeOpTargetTrafoBoxCox - Box-Cox Transform the Target Variable
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mlr_pipeops_fcst.targetdiffPipeOpTargetTrafoDifference - Difference the Target Variable
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mlr_pipeops_fcst.tsfeatsPipeOpFcstTsfeats - Time Series Feature Extraction
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selector_fcst_lags() - Select Forecast Lag Features
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selector_fcst_rolling() - Select Forecast Rolling Features
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as_learner_fcst() - Convert to a Forecast Learner
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as_task_fcst()as_tasks_fcst() - Convert to a Forecast Task
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autoplot(<TaskFcst>) - Plot for Forecast Tasks
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forecast(<Learner>) - Forecast from a Trained Learner
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generate_newdata() - Generate new data for a forecast task
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partition(<TaskFcst>) - Manually Partition into Training, Test and Validation Set
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read_tsf() - Read tsf files
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download_zenodo_record() - Download tsf file from Zenodo