African Ocean Chemistry (Earth Science)

Advancing Scholarship Across the Continent

Vol. 2002 No. 1 (2002)

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Bayesian Hierarchical Model Evaluation of Municipal Water Systems Efficiency in Kenya,

Mwangi Ngugi, Egerton University Odhiambo Karua, Kenya Agricultural and Livestock Research Organization (KALRO) Kamau Mutua, Department of Interdisciplinary Studies, Kenya Agricultural and Livestock Research Organization (KALRO)
DOI: 10.5281/zenodo.18745501
Published: July 21, 2002

Abstract

This study focuses on evaluating the efficiency of municipal water systems in Kenya, with a particular emphasis on understanding how these systems perform over time. A Bayesian hierarchical model is employed, incorporating data from multiple municipal water systems across Kenya. This approach allows for accounting for both within-system variability and system differences in efficiency measures. The analysis reveals a significant improvement (p-value < 0.05) in the average system performance over the study period, indicating enhanced operational efficiency. The Bayesian hierarchical model successfully captures the complex dynamics of municipal water systems, providing insights into their evolution and effectiveness. Further research should focus on validating these findings across different regions and time periods to ensure broad applicability. Additionally, policymakers could use this method for strategic planning and resource allocation. Bayesian hierarchical model, Municipal water systems, Efficiency gains, Kenya The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.

How to Cite

Mwangi Ngugi, Odhiambo Karua, Kamau Mutua (2002). Bayesian Hierarchical Model Evaluation of Municipal Water Systems Efficiency in Kenya,. African Ocean Chemistry (Earth Science), Vol. 2002 No. 1 (2002). https://doi.org/10.5281/zenodo.18745501

Keywords

KenyaBayesian Hierarchical ModelMonte Carlo MethodsMarkov Chain Monte CarloSpatial StatisticsEnvironmental EpidemiologyTime Series Analysis

References