Evaluation of statistical and machine learning models for time series prediction: Identifying the state-of-the-art and the best conditions for the use of each model.

•A systematic literature review of the last decade.•One of the most extensive, impartial and comprehensible evaluations ever done in the time series prediction field.•Recommendation of the most suitable predictors based on a critical analysis.•A guideline for models selection, parameters setting and validation of results.•A new online data repository for time series forecasting.