2017 Theses Doctoral

# Empirical Bayes, Bayes factors and deoxyribonucleic acid fingerprinting

The central theme in this thesis is Empirical Bayes. It starts off with application of Bayes and Empirical Bayes methods to deoxyribonucleic acid fingerprinting. Different Bayes factors are obtained and an alternative Bayes factor using the method of Savage is studied both for normal and non- normal priors. It then moves on to deeper methodological aspects of Empirical Bayes theory. A 1983 conjecture by Carl Morris on the parametric empirical Bayes prediction intervals for the normal regression model is studied and an improvement suggested. Carlin and Louis’ (1996) parametric empirical Bayes prediction interval for the same model is also dealt with analytically while their approach had been primarily numerical. It is seen that both of these intervals have the same coverage probability up to a certain order of approximation and they have the same expected length up to the same order of approximation. Both the intervals are equal tailed up to the same order of approximation. Then the corrected proof of an important published result by Datta, Ghosh and Mukerjee (2000) is provided using first principles of probability matching. This result is relevant to our work on parametric empirical Bayes prediction intervals.

## Subjects

## Files

- BASU_columbia_0054D_14236.pdf application/pdf 337 KB Download File

## More About This Work

- Academic Units
- Statistics
- Thesis Advisors
- Lo, Shaw-Hwa
- Degree
- Ph.D., Columbia University
- Published Here
- October 8, 2017