Traditional single-matrix Markov state models are biased even with infinite data; unbiased coarse-grained observables require separate equilibrium and A-to-B nonequilibrium transition matrices built from stationary within-cluster sampling.
Optimized parameter selection reveals trends in Markov state models for protein folding
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Markov state models revisited: Principles and algorithms for unbiased observables
Traditional single-matrix Markov state models are biased even with infinite data; unbiased coarse-grained observables require separate equilibrium and A-to-B nonequilibrium transition matrices built from stationary within-cluster sampling.