# Mixing it up: A general framework for Markovian statistics beyond reversibility and the minimax paradigm

@article{Dexheimer2020MixingIU, title={Mixing it up: A general framework for Markovian statistics beyond reversibility and the minimax paradigm}, author={Niklas Dexheimer and Claudia Strauch and Lukas Trottner}, journal={arXiv: Statistics Theory}, year={2020} }

Up to now, the nonparametric analysis of multidimensional continuous-time Markov processes has focussed strongly on specific model choices, mostly related to symmetry of the semigroup. While this approach allows to study the performance of estimators for the characteristics of the process in the minimax sense, it restricts the applicability of results to a rather constrained set of stochastic processes. In particular, among other drawbacks, it hardly allows incorporating jump structures. As a…

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