This work concerns controlled Markov chains with denumerable state space and discrete time parameter. The reward function is assumed to be≤0 and the performance of a control policy is measured by the expected total-reward criterion. Within this context, sufficient conditions are given so that...

We study controlled Markov chains with denumerable state space and bounded costs per stage. A (long-run) risk-sensitive average cost criterion, associated to an exponential utility function with a constant risk sensitivity coefficient, is used as a performance measure. The main assumption on the...

An autoregressive process of finite order is considered. In this context it is shown that Bartlett's formula for the asymptotic covariance matrix B of a vector of sample autocorrelations reduces to a matrix product, and a recursive method for computing B is given.