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"tsSelect Package - Pick the best time series model"

This package has as input a Time Series object.

The first step fits a series of models:

  • Mean model

  • Naive model (all forecasts = last observation)

  • Seasonal Naive model (each forecast is equal to the last observed value from the same season)

  • 'drift' model (adds a "trend" over time to the naive method)

  • tslm_1 (linear-regression by 'trend')

  • tslm_2 (linear-regression by 'trend' and 'season')

  • Exponential smoothing models (with several variations)

  • 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)

About

tsSelect R Package - Select the best forecast among several models. The package is implemented in

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