Strong Ratio Limit Theorems for Markov Processes
Lin, Michael
Ann. Math. Statist., Tome 43 (1972) no. 6, p. 569-579 / Harvested from Project Euclid
Let $P$ be a conservative and ergodic Markov operator on $L_\infty(X, \Sigma, m)$ (where $m(X) = 1$). It is proved that if for $A \in \Sigma$ with $m(A) > 0$ and $\mu \ll m$ a finite measure with $\mu(A) > 0 \lim_{n\rightarrow\infty} < \mu, P^{n+1}1_B >/<\mu, P^n 1_A>$ exists for every $B \subset A$, then $P$ has a $\sigma$-finite invariant measure $\lambda$ and there is a sequence $A_k \uparrow X$ with $A_0 = A$ such that for $0 \leqq f, g \in L_\infty(A_k) < \mu, P^n f>/<\mu, P^n g>\rightarrow < \lambda, f>/< \lambda, g>$. The result is used to study the convergence of $< \mu, P^n f>/< \eta, P^n g>$ for $\mu, \eta \ll m$, with applications to Harris processes and strong mixing point transformations. An analogous result for a positive contraction of $C(X)$ is given.
Publié le : 1972-04-14
Classification: 
@article{1177692637,
     author = {Lin, Michael},
     title = {Strong Ratio Limit Theorems for Markov Processes},
     journal = {Ann. Math. Statist.},
     volume = {43},
     number = {6},
     year = {1972},
     pages = { 569-579},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1177692637}
}
Lin, Michael. Strong Ratio Limit Theorems for Markov Processes. Ann. Math. Statist., Tome 43 (1972) no. 6, pp.  569-579. http://gdmltest.u-ga.fr/item/1177692637/