Incorporating prior information when true priors are unknown: An Information-Theoretic approach for increasing efficiency in estimation

- We develop a new way to incorporate priors when true priors are unobserved.
- We improve the efficiency of an Information-Theoretic method of inference.
- We use sampling experiments to show increase in efficiency for finite samples.
- Our new estimator dominates its other competitors.
- A relevant statistic for identifying the best model is developed.

We develop a new way to incorporate prior information within an Information-Theoretic (IT) estimation framework. The estimator considers many potential priors and uses a simple statistic to choose the optimal solution. Our method outperforms its competitors for all finite data.