The code uses mixtures of state space models to perform unsupervised clustering of short trajectories. Within the state space framework, we let expensive-to-gather biomarkers correspond to hidden states and readily obtainable cognitive metrics correspond to measurements. Upon training with expectation maximization, we often find that our clusters stratify persons according to clinical outcome. This code reproduces the figures in the accompanying manuscript.