FORECASTING OF AGRICULTURAL PRODUCTION INDICATORS IN SURKHANDARYA REGION USING THE ARIMA MODEL
DOI:
https://doi.org/10.5281/zenodo.21324207Keywords:
ARIMA model, forecasting, agricultural production, time series, stationarity, Augmented Dickey–Fuller test, autocorrelation, Surkhandarya regionAbstract
This article applies the ARIMA (1,2,0) model to forecast agricultural production in the
Surkhandarya region. The stationarity of the time series was examined using the Augmented Dickey–Fuller
test, while the model parameters were identified based on the ACF and PACF correlograms. Model reliability
was evaluated using the coefficient of determination, information criteria, and the Mean Absolute Percentage
Error (MAPE). The absence of autocorrelation was confirmed by the Ljung–Box test, whereas the absence of
heteroscedasticity was verified using the ARCH–LM test. Forecast values for 2026–2030 were estimated with
a 95% confidence interval
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