Nonparametric estimation of multivariate hidden Markov models using tensor-product B-splines
基于张量积 B 样条的多元隐马尔可夫模型非参数估计
For multivariate time series driven by underlying states, hidden Markov models (HMMs) constitute a powerful framework which can be flexibly tailored to the situation at hand. However, in practice it can be challenging to choose an adequate emission distribution for multivariate observation vectors. For example, the marginal data distribution may not immediately reveal the within-state distributional form, and also the different data streams may operate on different supports,…