pyemma.msm.cktest

pyemma.msm.cktest(msmobj, K, nsets=2, sets=None, full_output=False)

Chapman-Kolmogorov test for the given MSM

Parameters:

• msmobj (MSM or EstimatedMSM object) – Markov state model (MSM) object
• K (int) – number of time points for the test
• nsets (int, optional) – number of PCCA sets on which to perform the test
• sets (list, optional) – List of user defined sets for the test

Returns:

• p_MSM ((K, n_sets) ndarray) – p_MSM[k, l] is the probability of making a transition from set l to set l after k*lag steps for the MSM computed at 1*lag
• p_MD ((K, n_sets) ndarray) – p_MD[k, l] is the probability of making a transition from set l to set l after k*lag steps as estimated from the given data
• eps_MD ((K, n_sets)) – eps_MD[k, l] is an estimate for the statistical error of p_MD[k, l]
• set_factors ((K, nsets) ndarray, optional) – set_factor[k, i] is the quotient of the MD and the MSM set probabilities

References

[1]	Prinz, J H, H Wu, M Sarich, B Keller, M Senne, M Held, J D Chodera, C Schuette and F Noe. 2011. Markov models of molecular kinetics: Generation and validation. J Chem Phys 134: 174105