We have analyzed the timing and clustering properties of premature ventricular contractions (PVCs) of 184 post-infarction patients (from the Cardiac Arrhythmia Suppression Trial database, CAST). First, we transformed the heart beat annotations obtained from 24-h electrocardiogram recordings into symbol sequences where each heart beat was coded as an arrhythmic or as a normal beat. For these symbol sequences we explored (i) the Shannon entropy which was estimated in terms of the Lempel-Ziv complexity, (ii) the shape parameter of the Weibull distribution that best fits the PVC return times, and (iii) the strength of long-range correlations quantified by detrended fluctuation analysis (DFA). For the CAST data, we have found evidence for an intermediate strength of long-range correlations in the PVC timings, which are correlated to the age of the patient: younger post-infarction patients have higher strength of long-range correlations than older patients. The normalized Shannon entropy has values between 0.5 and 1.0 which indicates a high degree of randomness in the PVC timings. Second, we modelled our time series with a two-parametric peaks over the threshold (POT) model, interpreting each premature ventricular contraction (PVC) as an extreme event. We have found that in the frame of our model the Lempel-Ziv complexity is functionally related to the shape parameter of the Weibull distribution. Thus, two complementary measures (entropy and strength of long-range correlations) are sufficient to characterize realizations of the two-parametric model. For the CAST and the model data, the ranges of both measures were found to be in good accordance. The correlation between the age and the persistence strength found for the CAST data could be explained as a change of model parameters.