The Multiprocess Dynamic Linear Model with Biased Perturbations: A Real Time Model for Growth Hormone Level
将偏扰动分布引入多过程动态线性模型，用于实时检测动物生长激素水平中的脉冲信号，并在首次观测后立即更新参数估计和预测。
This paper introduces biased perturbation distributions into the multiprocess dynamic linear model in order to represent growth hormone levels in animals, which are characteristically noisy pulsatile time series. The use of biased perturbation distributions allows a pulse to be detected on the first observation immediately after it occurs, thus allowing the process to be modelled in real time. This approach is found to be quite effective at detecting the occurrence of a pulse in growth hormone level, and revising the parameter estimates and predictions accordingly.