STOCHASTIC MODELLING OF MONTHLY SUN BRIGHT IN COFFEE GROWING AREAS STOCHASTIC MODELLING OF MONTHLY SUN BRIGHT IN COFFEE GROWING AREAS
Autorregressive integrated moving average models ARIMA, were adjusted to series of monthly sun bright for 32 meteorological stations of The National Federation of Coffee Growers of Colombia. The structure of the adjusted models was ARIMA(0; 1; 1) * (0; 1; 1)12 this is a moving average with a seasona...
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| Format: | Article |
| Language: | English |
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Universidad Nacional de Colombia
2002-05-01
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| Series: | Revista Colombiana de Estadística |
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| Online Access: | http://www.revistas.unal.edu.co/index.php/estad/article/view/28548 |
| _version_ | 1828359388716335104 |
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| author | Chaves Bernardo |
| author_facet | Chaves Bernardo |
| author_sort | Chaves Bernardo |
| collection | DOAJ |
| description | Autorregressive integrated moving average models ARIMA, were adjusted to series of monthly sun bright for 32 meteorological stations of The National Federation of Coffee Growers of Colombia. The structure of the adjusted models was ARIMA(0; 1; 1) * (0; 1; 1)12 this is a moving average with a seasonality component each 12 month, the estimated parameters were sufficient to describe the behavior of the series, they were statistically different from zero and non correlated. The estimated forecasts were found very approximated to observed values, they are actualized monthly, this characteristic allow to readjust the model when the pattern series change and to plan activities related with absorption of solar energy. The greatest forecast error was 23% and it is considered acceptable.<br>Se ajustaron modelos ARIMA a series mensuales de brillo solar obtenidas en 32 estaciones meteorológicas de la Federación Nacional de Cafeteros de Colombia. La estructura de los modelos ajustados fue ARIMA(0; 1; 1)*(0; 1; 1)12 de promedios móviles con componente estacional de 12 meses. Los parámetros estimados fueron suficientes para describir el comportamiento de la serie. Los pronósticos obtenidos fueron muy cercanos de los valores observados, actualizados mensualmente. Esta característica permite reajustar el modelo cuando haya cambios en el patrón de la serie y planificar actividades relacionadas con la absorción de la energía solar. El mayor error de pronóstico fue de 23 %, considerado como aceptable. |
| first_indexed | 2024-04-14T03:41:51Z |
| format | Article |
| id | doaj.art-fd15a54fe3be4f58915f6d08fc51c65b |
| institution | Directory Open Access Journal |
| issn | 0120-1751 |
| language | English |
| last_indexed | 2024-04-14T03:41:51Z |
| publishDate | 2002-05-01 |
| publisher | Universidad Nacional de Colombia |
| record_format | Article |
| series | Revista Colombiana de Estadística |
| spelling | doaj.art-fd15a54fe3be4f58915f6d08fc51c65b2022-12-22T02:14:30ZengUniversidad Nacional de ColombiaRevista Colombiana de Estadística0120-17512002-05-012515971STOCHASTIC MODELLING OF MONTHLY SUN BRIGHT IN COFFEE GROWING AREAS STOCHASTIC MODELLING OF MONTHLY SUN BRIGHT IN COFFEE GROWING AREASChaves BernardoAutorregressive integrated moving average models ARIMA, were adjusted to series of monthly sun bright for 32 meteorological stations of The National Federation of Coffee Growers of Colombia. The structure of the adjusted models was ARIMA(0; 1; 1) * (0; 1; 1)12 this is a moving average with a seasonality component each 12 month, the estimated parameters were sufficient to describe the behavior of the series, they were statistically different from zero and non correlated. The estimated forecasts were found very approximated to observed values, they are actualized monthly, this characteristic allow to readjust the model when the pattern series change and to plan activities related with absorption of solar energy. The greatest forecast error was 23% and it is considered acceptable.<br>Se ajustaron modelos ARIMA a series mensuales de brillo solar obtenidas en 32 estaciones meteorológicas de la Federación Nacional de Cafeteros de Colombia. La estructura de los modelos ajustados fue ARIMA(0; 1; 1)*(0; 1; 1)12 de promedios móviles con componente estacional de 12 meses. Los parámetros estimados fueron suficientes para describir el comportamiento de la serie. Los pronósticos obtenidos fueron muy cercanos de los valores observados, actualizados mensualmente. Esta característica permite reajustar el modelo cuando haya cambios en el patrón de la serie y planificar actividades relacionadas con la absorción de la energía solar. El mayor error de pronóstico fue de 23 %, considerado como aceptable.http://www.revistas.unal.edu.co/index.php/estad/article/view/28548Stochastic modelARIMAtime seriessun bright |
| spellingShingle | Chaves Bernardo STOCHASTIC MODELLING OF MONTHLY SUN BRIGHT IN COFFEE GROWING AREAS STOCHASTIC MODELLING OF MONTHLY SUN BRIGHT IN COFFEE GROWING AREAS Revista Colombiana de Estadística Stochastic model ARIMA time series sun bright |
| title | STOCHASTIC MODELLING OF MONTHLY SUN BRIGHT IN COFFEE GROWING AREAS STOCHASTIC MODELLING OF MONTHLY SUN BRIGHT IN COFFEE GROWING AREAS |
| title_full | STOCHASTIC MODELLING OF MONTHLY SUN BRIGHT IN COFFEE GROWING AREAS STOCHASTIC MODELLING OF MONTHLY SUN BRIGHT IN COFFEE GROWING AREAS |
| title_fullStr | STOCHASTIC MODELLING OF MONTHLY SUN BRIGHT IN COFFEE GROWING AREAS STOCHASTIC MODELLING OF MONTHLY SUN BRIGHT IN COFFEE GROWING AREAS |
| title_full_unstemmed | STOCHASTIC MODELLING OF MONTHLY SUN BRIGHT IN COFFEE GROWING AREAS STOCHASTIC MODELLING OF MONTHLY SUN BRIGHT IN COFFEE GROWING AREAS |
| title_short | STOCHASTIC MODELLING OF MONTHLY SUN BRIGHT IN COFFEE GROWING AREAS STOCHASTIC MODELLING OF MONTHLY SUN BRIGHT IN COFFEE GROWING AREAS |
| title_sort | stochastic modelling of monthly sun bright in coffee growing areas stochastic modelling of monthly sun bright in coffee growing areas |
| topic | Stochastic model ARIMA time series sun bright |
| url | http://www.revistas.unal.edu.co/index.php/estad/article/view/28548 |
| work_keys_str_mv | AT chavesbernardo stochasticmodellingofmonthlysunbrightincoffeegrowingareasstochasticmodellingofmonthlysunbrightincoffeegrowingareas |