Prof. Balgobin Nandram
It is customary when presenting a choropleth map of rates or counts to present only the estimates (mean or mode) of the parameters of interest. While this technique illustrates spatial variation, it ignores the variation inherent in the estimates. We describe an approach to present variability in choropleth maps by constructing 100(1-alpha)% simultaneous intervals. The result provides three maps (estimate with two bands). We propose two methods to construct simultaneous intervals from the optimal individual highest posterior density (HPD) intervals to ensure joint simultaneous coverage of 100(1-alpha)%. Both methods exhibit the main feature of multiplying the lower bound and dividing the upper bound of the individual HPD intervals by parameters 0
Worcester Polytechnic Institute
All authors have granted to WPI a nonexclusive royalty-free license to distribute copies of the work. Copyright is held by the author or authors, with all rights reserved, unless otherwise noted. If you have any questions, please contact firstname.lastname@example.org.
Erhardt, Erik Barry, "Bayesian Simultaneous Intervals for Small Areas: An Application to Mapping Mortality Rates in U.S. Health Service Areas" (2004). Masters Theses (All Theses, All Years). 9.
Poisson-Gamma Regression, MCMC, Bayesian, Small Area Estimation, Simultaneous Inference, Statistics, Mappings (Mathematics), Mortality, Statistics, Mathematical models, Bayesian statistical decision theory, Poisson processes