The package provides a variety of functions to analysis several specific small area area-level
models in Bayesian context. Function BayesSAE specifies the model and obtain MCMC posterior draws.
summary, extract information from the returned object of class BayesSAE. replication
gives the replicated data which could be used for both numerical and graphical posterior checks. Function
mcmc generates the mcmc object of class which could be used for further MCMC diagnosis.
| Package: | BayesSAE |
| Type: | Package |
| Version: | 1.0 |
| Date: | 2013-08-17 |
| License: | GPL-2 |
This package provides functions for Bayesian analysis of small area models.
Bell, W. and Basel, W. and Cruse, C. and Dalzell, L. and Maples, J and O'Hara, B and Powers, D. (2007) Use of ACS Data to Produce SAIPE Model-Based Estimates of Poverty for Counties, U.S. Census official paper
Gelman, A. and Carlin, J. B. and Stern, H. S. and Rubin, D. B. (2006). Bayesian Data Analysis, CRC Press Company.
Hawalay, S. and Lahiriz, P. (2012). Hierarchical Bayes Estimation of Poverty Rates, U.S. Census companion paper
Rao, J. N. K. (2003) Small Area Estimation. John Wiley and Sons.
You, Y. and Chapman, B. (2006) Small Area Estimation Using Area Level Models and Estimated Sampling Variances. Survey Methodology, 32: 97-103.