Forecasting coconut production in the Philippines with ARIMA model
The study aimed to depict the situation of the coconut industry in the Philippines for the future years applying Autoregressive Integrated Moving Average (ARIMA) method. Data on coconut production, one of the major industrial crops of the country, for the period of 1990 to 2012 were analyzed using t...
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oai:animorepository.dlsu.edu.ph:faculty_research-101662024-03-26T07:23:30Z Forecasting coconut production in the Philippines with ARIMA model Lim, Cristina Teresa Natividad The study aimed to depict the situation of the coconut industry in the Philippines for the future years applying Autoregressive Integrated Moving Average (ARIMA) method. Data on coconut production, one of the major industrial crops of the country, for the period of 1990 to 2012 were analyzed using time-series methods. Autocorrelation (ACF) and partial autocorrelation functions (PACF) were calculated for the data. Appropriate Box-Jenkins autoregressive moving average model was fitted. Validity of the model was tested using standard statistical techniques. The forecasting power of autoregressive moving average (ARMA) model was used to forecast coconut production for the eight leading years. 2015-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/10336 Faculty Research Work Animo Repository Coconut industry—Philippines Agronomy and Crop Sciences |
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Coconut industry—Philippines Agronomy and Crop Sciences Lim, Cristina Teresa Natividad Forecasting coconut production in the Philippines with ARIMA model |
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The study aimed to depict the situation of the coconut industry in the Philippines for the future years applying Autoregressive Integrated Moving Average (ARIMA) method. Data on coconut production, one of the major industrial crops of the country, for the period of 1990 to 2012 were analyzed using time-series methods. Autocorrelation (ACF) and partial autocorrelation functions (PACF) were calculated for the data. Appropriate Box-Jenkins autoregressive moving average model was fitted. Validity of the model was tested using standard statistical techniques. The forecasting power of autoregressive moving average (ARMA) model was used to forecast coconut production for the eight leading years. |
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Lim, Cristina Teresa Natividad |
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Lim, Cristina Teresa Natividad |
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Lim, Cristina Teresa Natividad |
title |
Forecasting coconut production in the Philippines with ARIMA model |
title_short |
Forecasting coconut production in the Philippines with ARIMA model |
title_full |
Forecasting coconut production in the Philippines with ARIMA model |
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Forecasting coconut production in the Philippines with ARIMA model |
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Forecasting coconut production in the Philippines with ARIMA model |
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forecasting coconut production in the philippines with arima model |
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2015 |
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https://animorepository.dlsu.edu.ph/faculty_research/10336 |
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