Berkey C S
Biometrics. 1982 Dec;38(4):953-61.
Nonlinear least squares methods are currently used for fitting a well-known growth model, namely the Jenss model, to the length measurements of a child followed throughout the first six years of life. An empirical Bayes approach is developed for fitting the model, and the prior distribution of the growth-model parameters is estimated from a large sample of least squares parameters. An expression which is proportional to the posterior distribution is derived so that the posterior mode can be estimated. Given the observations on a child, this posterior mode provides Bayes estimates of the Jenss curve parameters for the child.
非线性最小二乘法目前用于将一个著名的生长模型，即延斯模型，拟合到跟踪一名儿童生命最初六年的身高测量数据上。本文开发了一种经验贝叶斯方法来拟合该模型，并从大量最小二乘参数样本中估计生长模型参数的先验分布。推导了一个与后验分布成比例的表达式，以便估计后验众数。给定一名儿童的观测数据，这个后验众数提供了该儿童延斯曲线参数的贝叶斯估计。
