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1رسالة جامعية
المؤلفون: Riba, Evans Mogolo
مرشدي الرسالة: Jankowitz, M. D.
مصطلحات موضوعية: Time series forecasting, Regression model with ARIMA errors, Autoregressive integrated moving averages, ARIMA, Artificial neural networks, ANN, Support vector machines, SVM, Bagging, Bootstrap aggregating, Air passengers, 387.70151955, Aeronautics, Commercial, South Africa, Passenger traffic, Forecasting, Air travel, Time-series analysis, Data processing
وصف الملف: 1 online resource (viii, 92 leaves, 3 unnumbered leaves) : illustrations, color graphs; application/pdf
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2
المؤلفون: Amezquita Bravo, Cristian Camilo
المساهمون: Moreno Rivas, Álvaro Martin
المصدر: Repositorio UN
Universidad Nacional de Colombia
instacron:Universidad Nacional de Colombiaمصطلحات موضوعية: Forecasting techniques, Air transport, Time series, Análisis de series de tiempo, 330 - Economía, Air passengers demand, Técnicas de predicción, ARIMA, Series de tiempo, SARIMA, Time-series analysis, Aviación comercial, Aeronautics, commercial, Pronóstico de demanda, ARIMAX, Transporte aéreo, Forecasting demand
وصف الملف: x, 46 páginas; application/pdf
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::7689e731c03cadf90d270c14d8c7b36eTest
https://repositorio.unal.edu.co/handle/unal/81124Test -
3رسالة جامعية
المؤلفون: Amezquita Bravo, Cristian Camilo
المساهمون: Moreno Rivas, Álvaro Martin
مصطلحات موضوعية: 330 - Economía, Time-series analysis, Aeronautics, commercial, Forecasting techniques, Análisis de series de tiempo, Aviación comercial, Técnicas de predicción, Pronóstico de demanda, Transporte aéreo, Series de tiempo, ARIMA, SARIMA, ARIMAX, Forecasting demand, Air transport, Air passengers demand, Time series
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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Evaluating time series models in short and long-term forecasting of Canadian air passenger data. No. 0306E, January 2003.; Franses, P. H. (1990). TESTING FOR SEASONAL UNIT ROOTS IN MONTHLY DATA. Erasmus University Rotterdam.; Goh, C., & Law, R. (2002). Modeling and forecasting tourism demand for arrivals with stochastic nonstationary seasonality and intervention. Tourism Management, 23(5), 499–510. https://doi.org/10.1016/S0261-5177Test(02)00009-2; Granger, C. W. J., & Newbold, P. (1974). Spurious Regressions in Econometrics. Journal of Econometrics, 2, 111–120. https://doi.org/10.1002/9780470996249.ch27Test; Greene, W. H. (1999). Análisis Econométrico (3rd ed.). Prentice Hall.; Gujarati, D., & Porter, D. (2010). Econometría (Quinta edi). McGraw Hill.; Hamilton, J. (1994). Time Series Analysis. Princeton University Press.; Harvey, A. C. (1993). Time Series Models. In Angewandte Chemie International Edition (2nd Editio, Vol. 6, Issue 11). MIT Press.; Hylleberg, S., Engle, R. 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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الإتاحة: https://doi.org/10.2307/2669794Test
https://doi.org/10.1177/0047287505279003Test
https://doi.org/10.1080/01621459.1971.10482227Test
https://doi.org/10.34096/rtt.i14.2432Test
https://doi.org/10.3143/geriatrics.57.contents2Test
https://doi.org/10.1080/00401706.1991.10484777Test
https://repositorio.unal.edu.co/handle/unal/81124Test
https://repositorio.unal.edu.coTest/