Estimating the transition matrix of a Markov chain observed at random times

We want to recover the transition kernel PP of a Markov chain XX when only a sub-sequence of XX is available. The time gaps between the observations are iid with unknown distribution. We propose a method to build an estimator of PP under the assumption that it has some zero entries. Its asymptotic performance is discussed in theory and through numerical simulations.