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    رسالة جامعية
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    رسالة جامعية

    المساهمون: Moreno Rivas, Álvaro Martin

    جغرافية الموضوع: Colombia

    وصف الملف: x, 46 páginas; application/pdf

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(2006). a Multivariate Arima Model To Forecast.; Artis, M. J., Clavel, J. G., Hoffmann, M., & Nachane, D. M. (2007). Harmonic Regression Models: A Comparative Review with Applications. SSRN Electronic Journal, 333. https://doi.org/10.2139/ssrn.1017519Test; Bloomfield, P. (2000). Fourier Analysis of Time Series: An Introduction. In Journal of the American Statistical Association (Vol. 95, Issue 452, p. 1373). https://doi.org/10.2307/2669794Test; Chatfield, C. (2000). Time-Series Forecasting. In Urologiia (Moscow, Russia : 1999) (Issue 1). Chapman & Hall/CRC. http://www.ncbi.nlm.nih.gov/pubmed/16856455Test; Chen, C. F., Chang, Y. H., & Chang, Y. W. (2009). Seasonal ARIMA forecasting of inbound air travel arrivals to Taiwan. Transportmetrica, 5(2), 125–140. https://doi.org/10.1080/18128600802591210Test; Chow, G. C., & Lin, A. (1971). Best Linear Unbiased Interpolation, Distribution, and Extrapolation of Time Series by Related Series. 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F., Granger, C. W. J., & Yoo, B. S. (1990). Seasonal integration and cointegration. Journal of Econometrics, 44(1–2), 215–238. https://doi.org/10.1016/0304-4076Test(90)90080-D; IATA. (2007). Aviation Economic Benefits. IATA Economics Briefing, N° 8.; IATA. (2020). Air connectivity: Measuring the connections that drive economic growth. 57(2), Contents2–Contents2. https://doi.org/10.3143/geriatrics.57.contents2Test; Kim, J. H., & Moosa, I. (2001). Seasonal behaviour of monthly international tourist flows: Specification and implications for forecasting models. Tourism Economics, 7(4), 381–396. https://doi.org/10.5367/000000001101297937Test; Lim, C., & Mcaleer, M. (2010). A seasonal analysis of Asian tourist arrivals to Australia. Applied Economics, 32(4), 499–509. https://doi.org/10.1080/000368400322660Test; Lim, C., & McAleer, M. (2001). Forecasting tourist arrivals. Annals of Tourism Research, 28(4), 965–977. https://doi.org/10.1016/S0160-7383Test(01)00006-8; Lin, C. J., Chen, H. F., & Lee, T. S. (2011). Forecasting Tourism Demand Using Time Series, Artificial Neural Networks and Multivariate Adaptive Regression Splines:Evidence from Taiwan. International Journal of Business Administration, 2(2). https://doi.org/10.5430/ijba.v2n2p14Test; Lutkepohl, H., & Kratzig, M. (2013). Applied Time Series Econometrics Time. In Journal of Chemical Information and Modeling (Vol. 53, Issue 9). Cambridge University Press.; Marazzo, M., Scherre, R., & Fernandes, E. (2010). Air transport demand and economic growth in Brazil: A time series analysis. Transportation Research Part E: Logistics and Transportation Review, 46(2), 261–269. https://doi.org/10.1016/j.tre.2009.08.008Test; Martínez-Ortíz, A., & García-Romero, H. (2016). Competitividad en el transporte aéreo en Colombia. 218. https://www.repository.fedesarrollo.org.co/bitstream/handle/11445/3280/Repor_Junio_2016_Martinez_y_Garcia.pdf?sequence=2&isAllowed=y&fbclid=IwAR2zdrF15WDXB7QHagHNepZLhhwPxF5nAE-06gXbchtCeFt6oq1I8ChgYGo%0Ahttp://www.repository.fedesarrollo.org.co/handle/11Test; Mogollón, J. D. (2020). Pronóstico de la demanda del transporte aéreo en aeropuerto distribuidor. Aplicación al caso de Aeropuerto Internacional el Dorado. 15, 1–137.; Nieto, M. R., & Carmona-Benítez, R. B. (2018). ARIMA + GARCH + Bootstrap forecasting method applied to the airline industry. Journal of Air Transport Management, 71(June), 1–8. https://doi.org/10.1016/j.jairtraman.2018.05.007Test; Oh, C. O., & Morzuch, B. J. (2005). Evaluating time-series models to forecast the demand for tourism in Singapore: Comparing within-sample and postsample results. 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