ON THE POPULATION DENSITY DISTRIBUTION ACROSS SPACE: A PROBABILISTIC APPROACH
在贝叶斯参数框架下，利用伽马分布研究区域人口密度分布，无需预先定义地域单元，并纳入个体偏好近似，以马萨诸塞州为例验证了主观距离测度对人口分布的良好拟合。
ABSTRACT Working within a Bayesian parametric framework, we develop a novel approach to studying the distribution of regional population density across space. By exploiting the Gamma distribution, we are able to introduce heterogeneity across space without incurring an a priori definition of territorial units. Our contribution also permits the inclusion of an approximation of individual preferences as a further driving force in location choices. We perform an empirical application to the case of Massachusetts. Our results demonstrate that a subjective measure of distance performs well in replicating the population distribution across Massachusetts.