标题： 动态有序回归关系的建模：加利福尼亚石斑鱼成熟度估计的应用 显示英文标题

标题： Modeling for Dynamic Ordinal Regression Relationships: An Application to Estimating Maturity of Rockfish in California

摘要： 我们开发了一个贝叶斯非参数框架，用于建模随离散时间演化的有序回归关系。 激发这一研究的应用问题涉及渔业研究中的一个关键问题，即估计年龄、长度和成熟度（后者以有序尺度记录）之间动态演化的相互关系。 该方法建立在协变量和潜在连续响应联合随机机制的非参数混合模型之上。 这种方法为有序回归函数提供了高度灵活的推断，同时避免了参数模型的计算挑战。 一种针对时间相关混合分布的新颖依赖性狄利克雷过程先验扩展了模型到动态设定。 该方法被用于详细研究加州海岸15年间采集数据的红辣椒石首鱼的成熟度、年龄和长度之间的关系。 显示英文摘要

摘要： We develop a Bayesian nonparametric framework for modeling ordinal regression relationships which evolve in discrete time. The motivating application involves a key problem in fisheries research on estimating dynamically evolving relationships between age, length and maturity, the latter recorded on an ordinal scale. The methodology builds from nonparametric mixture modeling for the joint stochastic mechanism of covariates and latent continuous responses. This approach yields highly flexible inference for ordinal regression functions while at the same time avoiding the computational challenges of parametric models. A novel dependent Dirichlet process prior for time-dependent mixing distributions extends the model to the dynamic setting. The methodology is used for a detailed study of relationships between maturity, age, and length for Chilipepper rockfish, using data collected over 15 years along the coast of California.