Author: Reinhard HöpfnerPublisher: American Mathematical Soc.
ISBN: 082183231X
Category : Mathematics
Languages : en
Pages : 105
Book Description
Limit Theorems for Null Recurrent Markov Processes
Author: Reinhard HöpfnerPublisher: American Mathematical Soc.
ISBN: 082183231X
Category : Mathematics
Languages : en
Pages : 105
Book Description
Limit Theorems for Null Recurrent Markov Processes
Author: Reinhard HöpfnerPublisher:
ISBN: 9781470403669
Category : Convergence
Languages : en
Pages : 105
Book Description
Conditioned Limit Theorems for Some Null Recurrent Markov Processes
Author: Richard DurrettPublisher:
ISBN:
Category : Limit theorems (Probability theory)
Languages : en
Pages : 158
Book Description
Let U sub k be a discrete time Markov process with state space E and let S be a proper subset of E. In several applications it is of interest to know the behavior of the system after a large number of steps given that the process has not entered S. for example if U sub k is a branching process a limit theorem of this type gives information about the size of the kth generation given that extinction has not occurred by time k.
Limit Theorems for Null Recurrent Markov Processes
Author: Reinhard HöpfnerLimit Theorems Involving Capacities for Recurrent Markov Chains
Author: Sidney C. PortPublisher:
ISBN:
Category : Markov processes
Languages : en
Pages : 68
Book Description
The asymptotic behavior of the quantity E(n) = The summation over all x of M(x) P sub x (V
Limit Theorems for Markov Chains and Stochastic Properties of Dynamical Systems by Quasi-Compactness
Author: Hubert HennionPublisher: Springer
ISBN: 3540446230
Category : Mathematics
Languages : en
Pages : 150
Book Description
The usefulness of from the of techniques perturbation theory operators, to kernel for limit theorems for a applied quasi-compact positive Q, obtaining Markov chains for stochastic of or dynamical by describing properties systems, of Perron- Frobenius has been demonstrated in several All use a operator, papers. these works share the features the features that must be same specific general ; used in each stem from the nature of the functional particular case precise space where the of is and from the number of quasi-compactness Q proved eigenvalues of of modulus 1. We here a functional framework for Q give general analytical this method and we the aforementioned behaviour within it. It asymptotic prove is worth that this framework is to allow the unified noticing sufficiently general treatment of all the cases considered in the literature the previously specific ; characters of model translate into the verification of of simple hypotheses every a functional nature. When to Markov kernels or to Perr- applied Lipschitz Frobenius associated with these statements rise operators expanding give maps, to new results and the of known The main clarify proofs already properties. of the deals with a Markov kernel for which 1 is a part quasi-compact Q paper of modulus 1. An essential but is not the simple eigenvalue unique eigenvalue element of the work is the of the of peripheral Q precise description spectrums and of its To conclude the the results obtained perturbations.
Uniform Limit Theorems for Markov Chains
Author: Shlomo LeventalSome Limit Theorems for Markov Chains and Related Occupancy Problems
Author: Burton Herbert SingerPublisher:
ISBN:
Category : Markov processes
Languages : en
Pages : 224
Book Description
Lecture Notes on Limit Theorems for Markov Chain Transition Probability Functions
Author: Steven OreyPublisher:
ISBN:
Category : Limit theorems (Probability theory)
Languages : en
Pages : 192
Book Description
Local Limit Theorems for Inhomogeneous Markov Chains
Author: Dmitry DolgopyatPublisher: Springer Nature
ISBN: 3031326016
Category : Mathematics
Languages : en
Pages : 348
Book Description
This book extends the local central limit theorem to Markov chains whose state spaces and transition probabilities are allowed to change in time. Such chains are used to model Markovian systems depending on external time-dependent parameters. The book develops a new general theory of local limit theorems for additive functionals of Markov chains, in the regimes of local, moderate, and large deviations, and provides nearly optimal conditions for the classical expansions, as well as asymptotic corrections when these conditions fail. Applications include local limit theorems for independent but not identically distributed random variables, Markov chains in random environments, and time-dependent perturbations of homogeneous Markov chains. The inclusion of appendices with background material, numerous examples, and an account of the historical background of the subject make this self-contained book accessible to graduate students. It will also be useful for researchers in probability and ergodic theory who are interested in asymptotic behaviors, Markov chains in random environments, random dynamical systems and non-stationary systems.