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利用逻辑斯蒂回归与汇总统计量的经验贝叶斯小区域估计AI 解读

Many available methods for estimating small area parameters are model-based, where auxiliary variables are used to predict the variable of interest. For nonlinear models, prediction is not straightforward. MacGibbon and Tomberlin (1989) and Farrell, MacGibbon, and Tomberlin (1994) have proposed methods which require micro-data for each individual in a small area. Here, the authors use a second-order Taylor series expansion to obtain model-based predictions which only require…

交叉分类下的保险损失预测：不同方法的比较AI 解读

Various mathematical and statistical models for estimation of automobile insurance pricing are reviewed. The methods are compared on their predictive ability based on two sets of automobile insurance data for two different states collected over two different periods. The issue of model complexity versus data availability is resolved through a comparison of the accuracy of prediction. The models reviewed range from the use of simple cell means to various…