A eural network model for the Quarterly Index of Total Construction in Spain
DOI:
https://doi.org/10.54571/ajee.437Keywords:
Total Quarterly Construction Index of Spain, neural netwoks models, OECD, forecasts, statistical package R, statistical package forecastAbstract
Using the quarterly Index of Total Construction in Spain, a neural network model is presented to envision the future of construction in Spain, from the third quarter of 2019 to the second quarter of 2022.
Downloads
References
VIII. Bibliografía
CRAN, The Comprehensive R Archive Network. https://cloud.r-project.org/
Efron, B. y Hastie, T., Computer Age Statistical Inference, Algorithms, Evidence, and Data Science, Cambridge University Press, New York, 2016. DOI: https://doi.org/10.1017/CBO9781316576533
García Delgado, J. L. y Myro, R., directores, Lecciones de Economía Española, 13ª edición, Civitas (Thomson Reuters), Editorial Aranzadi, Cizur Menor(Navarra), 2017.
Hyndman, R. J. y Athanasopoulus, G., Forecasting, Principles and Practice, segunda edición, OTexts.org, 2018.
Hyndman, R. J. y Athanosopoulos, G., paquete fpp2, en CRAN. Este paquete estadístico acompaña a la obra Forecasting, Principles and Practice, segunda edición.
James, G., Witten, D,, Hastie, T. y Tibshirani, R., An Introduction to Statistical Learning with Applications in R, Springer, New York, 2013. DOI: https://doi.org/10.1007/978-1-4614-7138-7
Kourentzes, N., package nnfor, en CRAN. Este paquete estadístico complementa: Ord, K., Fildes, R. y Kourentzes, N., Principles of Business Forecasting, segunda edición, Wesssex Press Inc., New York, 2017.
Matloff, N., Statistical Regression and Classification, From Linear Models to Machine Learning, CRC Press, Boca Raton, 2017. DOI: https://doi.org/10.1201/9781315119588
Matloff, N., Probability and Statistics for Data Science, Math + R + Data, CRC Press, Boca Raton, 2020. DOI: https://doi.org/10.1201/9780429401862
OECD, Organization for Economic Cooperation and Development, Production of Total Construction in Spain,[ESPROCONQISMEI], datos tomados del Federal Reserve Bank of St. Louis, https://fred.stlouisfed.org/series/ESPROCONQISMEI, septiembre 18, 2019.
Ord, K., Fildes, R. y Kourentzes, N., Principles of Business Forecasting, segunda edición, Wessex Press Inc., New York, 2017.
R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
Ramsundar, B. y Zadeh, R. B., TensorFlow for Deep Learning, O’Reilly, Sebastopol, CA, 2018.
Tsay, R. S., Analysis of Financial Time Series, J. Wiley and Sons, Inc., Hoboken, 2010. DOI: https://doi.org/10.1002/9780470644560