**DESCRIPTION OF COURSES**

**AS 668 BAYESIAN INFERENCE IN SURVEY SAMPLING (1L+1P) III**

**Objective**

The students would be exposed to the advanced concepts of Bayesian Inference in Survey Sampling. This course prepares students for undertaking research in this area.

**Theory**

UNIT I

Super population models in sample surveys. Stochastic parameter models. Bayes’ linear predictor, Bayesian models with multi-stage sampling. Measurement error and small area estimation.

UNIT II

Time series approach in survey sampling. Dynamic Bayesian prediction, Kalman filter, empirical and hierarchical Bayes predictors. Robust linear prediction, Bayesian robustness.

**Practicals**

Stochastic parameter models, Bayes’ linear predictor, Kalman filter, Empirical and Hierarchical Bayes predictors, Robust linear prediction.

**Suggested Readings**

- Berger, J.O. 1993.
*Statistical Decision Theory and Bayesian Analysis*. Springer. - Bolfarine, H. and Zacks, S. 1992.
*Prediction Theory for Finite Population Sampling*. Springer. - Cassel, C.M., Sarndal, C.E. and Wretman, J.H. 1977.
*Foundations of Inference in Survey Sampling*. John Wiley. - Des Raj and Chandhok, P. 1998.
*Sample Survey Theory*. Narosa Publishing House. - Ghosh, M. and Meeden, G. 1997.
*Bayesian Method for Finite Population Sampling. Monograph on Statistics and Applied Probability*. Chapman and Hall. - Mukhopadhyay, P. 1998.
*Theory and Methods of Survey Sampling*. Prentice Hall of India. - Rao, J. N. K. 2003.
*Small Area Estimation*. John Wiley. - Sarndal, C.E., Swensson, B. and Wretman, J. H. 1992.
*Model Assisted Survey Sampling*. Springer.