Forecasting of Monthly Rainfall in Dir (L) KP Pakistan With ARMA Models
DOI:
https://doi.org/10.62345/jads.2025.14.1.57Keywords:
Ljung-Box Test, Forecast Accuracy, Rainfall Forecasting, ARMA Models, Time Series Analysis Box-Jenkins Methodology, Time Series AnalysisAbstract
This study focuses on forecasting monthly mean rainfall in District Dir (Lower) using various ARMA models to identify the most suitable approach for accurate rainfall prediction. Rainfall forecasting is a critical and intriguing area of study, and the Box-Jenkins methodology, which employs ARMA models, is highly effective for analyzing and forecasting time series with diverse patterns of variation. The ARMA modeling process involves defining, estimating, diagnosing, and forecasting stages, making it well-suited for this application. Based on the analysis, the ARMA (4,4) model emerged as the best fit for the dataset, evaluated using SIGMASQ, AIC, and SC criteria, which yielded the smallest values and confirmed through the Ljung-Box Q-test. Using the ARMA (4,4) model, the study successfully forecasted monthly mean rainfall in District Dir (lower) from June 2022 to May 2028.
Downloads
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
License Terms
All articles published by Centre for Research on Poverty and Attitude are made immediately available worldwide under an open access license. This means:
- everyone has free and unlimited access to the full-text of all articles published in Centre for Research on Poverty and Attitude's journals;
- everyone is free to re-use the published material if proper accreditation/citation of the original publication is given.
