Identifying regime switches through Bayesian wavelet estimation: evidence from flood detection in the Taquari River Valley
通过贝叶斯小波估计识别状态切换：塔夸里河谷洪水检测
Two-component mixture models have proved to be a powerful tool for modeling heterogeneity in several cluster analysis contexts. However, most methods based on these models assume a constant behavior for the mixture weights, which can be restrictive and unsuitable for some applications. In this paper, we relax this assumption and allow the mixture weights to vary according to the index (e.g., time) to make the model more adaptive to a broader range of data sets. We propose an…