African Geometry and Topology (Pure Science) | 03 July 2010
Regularity and Model Selection in Time-Series Econometrics for Traffic Flow Optimization in Tanzania
S, a, m, u, e, l, s, K, a, c, h, i, m, b, a, ,, S, i, m, a, n, i, N, d, e, g, e, ,, K, a, m, a, l, i, M, w, a, k, w, e, r, e, ,, M, u, n, y, u, a, O, m, b, i, r, i
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.