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This research assesses the efficiency of regional monitoring networks in Ghana over time.

March 7, 2026Open Access

Regional Monitoring Networks Efficiency Assessment Using Time-Series Forecasting Models in Ghana,

Key Points

This research assesses the efficiency of regional monitoring networks in Ghana over time.
Utilized ARIMA model for time-series forecasting of network efficiency.
Conducted a comprehensive analysis with robust standard errors for inference.
Evaluated model performance using out-of-sample error metrics.
ARIMA model indicated a significant upward trend in network performance.
Estimated increase of 15% in network efficiency over the study period.
Findings highlight the effectiveness of time-series forecasting in improving network efficiency.

Abstract

This study examines regional monitoring networks in Ghana to evaluate their efficiency over time. A comprehensive analysis was conducted using ARIMA (AutoRegressive Integrated Moving Average) model to forecast network efficiency trends in Ghana. Robust standard errors were used for inference. The ARIMA model showed a significant upward trend in network performance, with an estimated increase of 15% over the study period. The findings suggest that time-series forecasting can effectively measure and improve the efficiency of regional monitoring networks in Ghana. Future research should explore integrating machine learning models to enhance predictive accuracy. Model estimation used =argmin_ᵢ (yᵢ, f_ (xᵢ) ) +₂², with performance evaluated using out-of-sample error.

Regional Monitoring Networks Efficiency Assessment Using Time-Series Forecasting Models in Ghana,

Key Points

Abstract

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