Squaring and adding $\pm 1$ mod p generates a curiously intractable random walk. A similar process over the finite field $\mathbf{F}_q$ (with $q=2^d$) leads to novel connections between elementary Galois theory probability.

Markov chain Monte Carlo (MCMC) algorithms are generally regarded as the gold standard technique for Bayesian inference. They theoretically well-understood and conceptually simple to apply in practice. The drawback of MCMC is that performing exact inference requires all data be processed at each iteration algorithm. For large datasets, computational cost can prohibitive, which has led recent de...

We prove that under a mild positivity assumption the entropy rate of a hidden Markov chain varies analytically as a function of the underlying Markov chain parameters. We give examples to show how this can fail in some cases. And we study two natural special classes of hidden Markov chains in more detail: binary hidden Markov chains with an unambiguous symbol and binary Markov chains corrupted ...

We prove that under a mild positivity assumption the entropy rate of a hidden Markov chain varies analytically as a function of the underlying Markov chain parameters. We give examples to show how this can fail in some cases. And we study two natural special classes of hidden Markov chains in more detail: binary hidden Markov chains with an unambiguous symbol and binary Markov chains corrupted ...

Suppose C is a closed recurrent communicating class for a Markov chain, if we restrict the chain on this class, the result is still a Markov chain with state space C. The resulting Markov chain is irreducible and recurrent. In this lecture, we will focus on the long-time behavior of irreducible and recurrent Markov chain. First, we have the following related definition. Definition 10.1. For a M...