Modeling for Dynamic Ordinal Regression Relationships: An Application to Estimating Maturity of Rockfish in California
动态有序回归关系建模：加州岩鱼成熟度估计
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…