Log-Linear Models for Doubly Sampled Categorical Data Fitted by the EM Algorithm
将双重抽样实验表示为不完整的多维列联表，用对数线性模型和EM算法进行最大似然估计，适用于任意因子数和测量设备的实验。
Abstract Double-sampling experiments can be expressed as incomplete multiway contingency tables and analyzed by using techniques appropriate for fitting log-linear models. The framework described can be applied to experiments with any number of factors and measurement devices. Maximum likelihood estimation via the EM algorithm leads to straightforward expressions for covariances of estimates of the parameters and functions of the parameters.