Maximum Likelihood for Generalized Linear Models with Nested Random Effects via High-Order, Multivariate Laplace Approximation
提出一种高阶多元拉普拉斯逼近方法，用于含嵌套随机效应的广义线性模型的最大似然估计，提高了计算精度和效率。
Stephen W. Raudenbush, Meng-Li Yang, Matheos Yosef, Maximum Likelihood for Generalized Linear Models with Nested Random Effects via High-Order, Multivariate Laplace Approximation, Journal of Computational and Graphical Statistics, Vol. 9, No. 1 (Mar., 2000), pp. 141-157