Artificial Neural Network with Histogram Data Time Series Forecasting: A Least Squares Approach Based on Wasserstein Distance

Author:

Rakpho Pichayakone,Yamaka Woraphon,Zhu Kongliang

Publisher

Springer International Publishing

Reference16 articles.

1. Arroyo, J., Maté, C.: Forecasting histogram time series with k-nearest neighbours methods. Int. J. Forecast. 25(1), 192–207 (2009)

2. Arroyo, J., González-Rivera, G., Maté, C.: Forecasting with interval and histogram data. Some financial applications. Handbook of empirical economics and finance, pp. 247–280 (2010)

3. Billard, L., Diday, E.: Symbolic Data Analysis: Conceptual Statistics and Data Mining. Wiley, Hoboken (2006)

4. Dias, S., Brito, P.: A new linear regression model for histogram-valued variables. In: 58th ISI World Statistics Congress, Dublin, Ireland (2011). http://isi2011.congressplanner.eu/pdfs/950662.pdf

5. Dias, S., Brito, P.: Linear regression model with histogram–valued variables. Statistical Analysis and Data Mining: The ASA Data Science Journal, 8(2), 75–113 (2015). Dueker, M.J.: Markov switching in GARCH processes and mean-reverting stock-market volatility. Journal of Business and Economic Statistics, 15(1), 26–34 (1997)

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