Growth curves are commonly used in modeling aimed at crop yield prediction. Fitting such curves often depends on availability of detailed observations, such as individual grape bunch weight or individual apple weight. However, in practice, aggregated weights (such as a bucket of grape bunches or apples) are available instead. While treating such bucket averages as if they were individual observations is tempting, it may introduce bias particularly with respect to population variance. In this paper we provide an elegant solution which enables estimation of individual weights using Dirichlet priors within Bayesian inferential framework.

翻译：成长曲线通常用于预测作物收成。拟合这样的曲线通常依赖于详细观察数据的可用性，例如单个葡萄串重量或单个苹果重量。然而，实际上只有聚合重量（如一桶葡萄串或苹果）是可以获得的。把这样的聚合平均值视为是否为单个观测可能会引入偏差，特别是关于总体方差的偏差。在本文中，我们提供了一种优雅的解决方案，使用Dirichlet先验在贝叶斯推理框架内估计单个重量。