This package has as input a Time Series object.
The first step fits a series of models:
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Mean model
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Naive model (all forecasts = last observation)
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Seasonal Naive model (each forecast is equal to the last observed value from the same season)
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'drift' model (adds a "trend" over time to the naive method)
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tslm_1 (linear-regression by 'trend')
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tslm_2 (linear-regression by 'trend' and 'season')
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Exponential smoothing models (with several variations)
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ARIMA (with and without stepwise selection)
The second step picks the model with lowest error measures, either by a specific measure or by majority vote, among all possible error measures.
The different error measures are: ME, RMSE, MAE, MPE ,MAPE, MASE, ACF1
Execution example:
library(tsSelect)
run_models(ts_object)