Feature-Based Forecast Model Selection

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Documentation for package ‘seer’ version 1.1.8

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accuracy_arima Calculate accuracy measue based on ARIMA models
accuracy_ets Forecast-accuracy calculation
accuracy_mstl Calculate accuracy based on MSTL
accuracy_nn Calculate accuracy measure calculated based on neural network forecasts
accuracy_rw Calculate accuracy measure based on random walk models
accuracy_rwd Calculate accuracy measure based on random walk with drift
accuracy_snaive Calculate accuracy measure based on snaive method
accuracy_stlar Calculate accuracy measure based on STL-AR method
accuracy_tbats Calculate accuracy measure based on TBATS
accuracy_theta Calculate accuracy measure based on Theta method
accuracy_wn Calculate accuracy measure based on white noise process
acf5 Autocorrelation-based features
acf_seasonalDiff Autocorrelation coefficients based on seasonally differenced series
build_rf build random forest classifier
cal_features Calculate features for new time series instances
cal_m4measures Mean of MASE and sMAPE
cal_MASE Mean Absolute Scaled Error(MASE)
cal_medianscaled scale MASE and sMAPE by median
cal_sMAPE symmetric Mean Absolute Pecentage Error(sMAPE)
cal_WA Weighted Average
classify_labels Classify labels according to the FFORMS famework
classlabel identify the best forecasting method
combination_forecast_inside This function is call to be inside fforms_combination
convert_msts Convert multiple frequency time series into msts object
e_acf1 Autocorrelation coefficient at lag 1 of the residuals
fcast_accuracy calculate forecast accuracy from different forecasting methods
fforms_combinationforecast Combination forecast based on fforms
fforms_ensemble Function to identify models to compute combination forecast using FFORMS algorithm
holtWinter_parameters Parameter estimates of Holt-Winters seasonal method
prepare_trainingset preparation of training set
rf_forecast function to calculate point forecast, 95% confidence intervals, forecast-accuracy for new series
sim_arimabased Simulate time series based on ARIMA models
sim_etsbased Simulate time series based on ETS models
sim_mstlbased Simulate time series based on multiple seasonal decomposition
split_names split the names of ARIMA and ETS models
stlar STL-AR method
unitroot Unit root test statistics