Generalized information criteria for high-dimensional sparse statistical jump models
We extend the generalized information criteria framework for model selection to high-dimensional sparse statistical jump models, a recent class of statistically robust and computationally efficient alternatives to hidden Markov models. Specifically, we derive expressions for the model fit and complexity to construct suitable information criteria for hyperparameter selection. In extensive simulatio
