We study the infinitesimal generators of evolutions of linear mappings on the space of polynomials, which correspond to a special class of Markov processes with polynomial regressions called quadratic harnesses. We relate the infinitesimal generator to the unique solution of a certain commutation equation, and we use the commutation equation to find an explicit formula for the infinitesimal generator of free quadratic harnesses.

Sensitivity analysis of irreducible Markov chains considers an original Markov chain with transition probability matrix $P$ and modified Markov chain with transition probability matrix $P$. For their respective stationary probability vectors $\pi ,\tilde{\pi }$, some of the following charactristics are usually studied: $\parallel \pi -\tilde{\pi }{\parallel }_p$ for asymptotical stability [3], $|{\pi }_i-{\tilde{\pi }}_i|,\frac{|{\pi }_i-{\tilde{\pi }}_i|}{{\pi }_i}$ for componentwise stability or sensitivity [1]. For functional transition probabilities, $P=P\left(t\right)$ and stationary probability vector $\pi \left(t\right)$, derivatives are also used for studying...

It has been known for a long time that for birth-and-death processes started in zero the first passage time of a given level is distributed as a sum of independent exponentially distributed random variables, the parameters of which are the negatives of the eigenvalues of the stopped process. Recently, Diaconis and Miclo have given a probabilistic proof of this fact by constructing a coupling between a general birth-and-death process and a process whose birth rates are the negatives of the eigenvalues,...

It is known that the time until a birth and death process reaches a certain level is distributed as a sum of independent exponential random variables. Diaconis, Miclo and Swart gave a probabilistic proof of this fact by coupling the birth and death process with a pure birth process such that the two processes reach the given level at the same time. Their coupling is of a special type called intertwining of Markov processes. We apply this technique to couple the Wright-Fisher diffusion with reflection...