predtoolsTS: R package for streamlining time series forecasting

Francisco Charte1, A. Vico1, María Dolores Pérez-Godoy1, Antonio J. Rivera1
1Dasci Andalusian Institute of Data Science and Computational Intelligence, Universidad de Jaén, Jaén, Spain

Tóm tắt

Từ khóa


Tài liệu tham khảo

Barboza, F., Kimura, H., Altman, E.: Machine learning models and bankruptcy prediction. Expert Syst. Appl. 83, 405–417 (2017)

Bollerslev, T.: Generalized autoregressive conditional heteroskedasticity. J. Econom. 31(3), 307–327 (1986)

Box, G.E.P., Jenkins, G.M., Reinsel, G.C.: Time Series Analysis: Forecasting and Control, 4th edn. Wiley, Hoboken (2008)

Brockwell, P.J., Davis, R.A., Calder, M.V.: Introduction to Time Series and Forecasting, vol. 2. Springer, Berlin (2002)

Das, S.: Time Series Analysis. Princeton University Press, Princeton (1994)

De Gooijer, J.G., Hyndman, R.J.: 25 years of time series forecasting. Int. J. Forecast. 22(3), 443–473 (2006)

Deb, C., Zhang, F., Yang, J., Lee, S.E., Shah, K.W.: A review on time series forecasting techniques for building energy consumption. Renew. Sustain. Energy Rev. 74, 902–924 (2017)

Doukhan, P.: Stochastic Models for Time Series, vol. 80. Springer, Berlin (2018)

Fiorucci, J.A., Louzada, F., Yiqi, B., Fiorucci, M.J.A.: Package ‘forectheta’ (2016)

Hyndman, R.J., Khandakar, Y.: Automatic time series forecasting: the forecast package for R. J. Stat. Softw. 26(3), 1–22 (2008)

Kourentzes, N., Petropoulos, F., Trapero, J.R.: Improving forecasting by estimating time series structural components across multiple frequencies. Int. J. Forecast. 30(2), 593 (2014)

Kuhn, M., et al.: Building predictive models in r using the caret package. J. Stat. Softw. 28(5), 1–26 (2008)

McLeod, A.I., Zhang, Y.: Faster arma maximum likelihood estimation. Comput. Stat. Data Anal. 52(4), 2166–2176 (2007)

McLeod, A.I., Yu, H., Mahdi, E.: Time series analysis with r. In: Subba Rao, T., Subba Rao, S., Rao, C.R. (eds.) Handbook of Statistics, vol. 30, pp. 661–712. Elsevier, Amsterdam (2012)

Naing, W.Y.N., Htike, Z.Z.: State of the art machine learning techniques for time series forecasting: a survey. Adv. Sci. Lett. 21(11), 3574–3576 (2015)

Ryan, J.A., Ulrich, J.M.: xts: Extensible Time Series. R package version 0.8-2 (2011)

Tashman, L.J.: Out-of-sample tests of forecasting accuracy: an analysis and review. Int. J. Forecast. 16(4), 437–450 (2000)

Trapletti, A., Hornik, K.: tseries: Time Series Analysis and Computational Finance (2018). R package version 0.10-46

Weiss, C.E., Raviv, E., Roetzer, G.: Forecast combinations in r using the forecastcomb package. R J. 10(2), 262–281 (2018)

Zecchin, C., Facchinetti, A., Sparacino, G., Cobelli, C.: Jump neural network for online short-time prediction of blood glucose from continuous monitoring sensors and meal information. Comput. Methods Progr. Biomed. 113(1), 144–152 (2014)

Zeileis, A., Grothendieck, G.: Zoo: S3 infrastructure for regular and irregular time series. J. Stat. Softw. 14(6), 1–27 (2005)