Vol. 2010 No. 1 (2010)

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Regularity and Model Selection in Time-Series Econometrics for Traffic Flow Optimization in Tanzania

Samuels Kachimba, Mkwawa University College of Education Simani Ndege, Department of Interdisciplinary Studies, Mkwawa University College of Education Kamali Mwakwere, Department of Advanced Studies, Tanzania Commission for Science and Technology (COSTECH) Munyua Ombiri, Department of Research, University of Dar es Salaam
DOI: 10.5281/zenodo.18907266
Published: May 6, 2010

Abstract

Traffic flow optimization in Tanzania is critical for improving road safety and reducing congestion. Regularization will be applied using LASSO (Least Absolute Shrinkage and Selection Operator) method to select the most relevant variables affecting traffic flow. Cross-validation procedures will be used to ensure optimal model performance. This theoretical framework provides a robust method for optimising traffic flow in Tanzania by identifying key influencing factors using econometric models. Policy makers should consider implementing these model selection methods to enhance traffic management systems and reduce congestion. Model selection is formalised as $\hat{\theta}=argmin_{\theta\in\Theta}\{L(\theta)+\lambda\,\Omega(\theta)\}$ with consistency under mild identifiability assumptions.

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How to Cite

Samuels Kachimba, Simani Ndege, Kamali Mwakwere, Munyua Ombiri (2010). Regularity and Model Selection in Time-Series Econometrics for Traffic Flow Optimization in Tanzania. African Geometry and Topology (Pure Science), Vol. 2010 No. 1 (2010). https://doi.org/10.5281/zenodo.18907266

Keywords

TanzaniaTime-Series EconometricsRegularizationLASSOModel SelectionAutoregressionForecasting

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Vol. 2010 No. 1 (2010)
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African Geometry and Topology (Pure Science)

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