BAYESIAN SMOOTHING OF RATES IN SMALL GEOGRAPHIC AREAS*
提出一种贝叶斯统计方法，用于平滑小地理区域（如县）的原始比率（如失业率、人均收入），并以1980年美国人口普查的低估率数据为例说明该方法。
ABSTRACT. An enormous amount of socio‐economic and public‐health data come as rates (e.g., unemployment, per capita income, mortality rates, census undercount) reported in small geographic areas. The U.S. Census Bureau regularly publishes data series at the county level, although the county is often a small area chosen for administrative convenience rather than by design. The reported rates can be regarded as a noisy representation of the true geographic distribution of rates over the small areas. This article presents a Bayesian statistical method of smoothing raw rates. In order to illustrate the important features of the method, a data set on undercoverage in the 1980 U.S. Census will be used.