Sample interview questions: How do you approach the process of calibrating and validating theoretical models with observational data?
Sample answer:
Calibration and Validation of Theoretical Models with Observational Data
- Model Selection: Determine the appropriate theoretical model based on available data and physical understanding.
- Parameter Optimization: Calibrate model parameters by minimizing the discrepancy between model predictions and observational data. This can involve iterative methods such as Markov Chain Monte Carlo (MCMC) or Bayesian inference.
- Cross-Validation: Divide data into training and testing sets. Calibrate the model on the training set and evaluate its performance on the testing set to avoid overfitting.
- Comparison with Multiple Models: Consider different theoretical models and compare their predictions against observational data. This helps assess the robustness and uniqueness of the selected model.
- Independent Data Checks: Obtain additional observational data or independent measurements to further validate the model.
- Physical Consistency: Verify that the calibrated model adheres to fund… Read full answer
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