SEIR 3-Parameter Grid Search
Fit β (transmission), σ (incubation), and γ (recovery) simultaneously
Given Parameter Ranges
β (transmission):
[0.3, 0.7]
σ (incubation):
[0.1, 0.3]
γ (recovery):
[0.05, 0.25]
Grid resolution:
15 points/param
Total evaluations:
3,375
Comparison: Your Choice vs. Grid Search Optimum
Your Manual Selection:
β = -
(Error: -)
σ = -
(Error: -)
γ = -
(Error: -)
SSE: -
Grid Search Optimum:
β = -
(Error: -)
σ = -
(Error: -)
γ = -
(Error: -)
SSE: -
Performance Comparison:
Grid search improved SSE by -
(-% reduction)
True parameters: β = 0.420, σ = 0.180, γ = 0.110
Model Fit to Data
Red dots are the observed data used to calculate SSE = Σ(Iobs - Imodel)²
2D Parameter Slice (SSE Landscape)
Run grid search to visualize parameter landscape
Red circle highlights the minimum SSE in this slice
Key Learning Points:
- Objective: Minimize SSE = Σ(Iobserved - Imodel)² over 3-parameter space
- Grid search: Systematically evaluates all parameter combinations in given ranges
- Computational cost: O(n³) for 3 parameters - scales poorly to higher dimensions
- Clean data advantage: Clear global minimum, all parameters identifiable
- Parameter effects: β controls peak height, σ delays onset, γ extends duration
- 2D slices: Visualize how SSE varies when fixing one parameter at its optimal value