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math.ST2026
Discrete-time, discrete-state multistate Markov models from the perspective of algebraic statistics
Dario Gasbarra, Kaie Kubjas, Sangita Kulathinal +3
We study discrete-time, discrete-state multistate Markov models from the perspective of algebraic statistics. These models are widely studied in event history analysis, and are cha…
math.ST2026
Identifiability in Graphical Discrete Lyapunov Models
Cecilie Olesen Recke, Sarah Lumpp, Nataliia Kushnerchuk +4
In this paper, we study discrete Lyapunov models, which consist of steady-state distributions of first-order vector autoregressive models. The parameter matrix of such a model enco…
math.ST2024
Matroid Stratification of ML Degrees of Independence Models
Oliver Clarke, Serkan HoÅten, Nataliia Kushnerchuk +1
We study the maximum likelihood (ML) degree of discrete exponential independence models and models defined by the second hypersimplex. For models with two independent variables, we…