Results 61 to 70 of about 120 (114)

Hidden Markov Model Regression

open access: yes, 1993
Hidden Markov Model Regression (HMMR) is an extension of the Hidden Markov Model (HMM) to regression analysis. We assume that the parameters of the regression model are determined by the outcome of a finite-state Markov chain and that the error terms are
Fridman, Moshe, Moshe Fridman
core  

Markov Chain Sensitivity Measured By Mean First Passage Times

open access: yes, 1999
The purpose of this article is to present results concerning the sensitivity of the stationary probabilities for a n-state, time-homogeneous, irreducible Markov chain in terms of the mean first passage times in the chain. Key words.
Grace E. Cho, Carl D. Meyer
core  

Uniform ergodicities and perturbation bounds of Markov chains on base norm spaces

open access: yes, 2018
It is known that Dobrushin's ergodicity coefficient is one of the effective tools in the investigations of limiting behavior of Markov processes. Several interesting properties of the ergodicity coefficient of a positive mapping defined on base norm ...
Mukhamedov, Farrukh   +1 more
core  

Reliable uncertainties of tests and surveys – a data-driven approach [PDF]

open access: yes
MSC Classification 60J10, 91Exx, 91E45, 05A18.Supplementary material are available online at: https://www.metrology-journal.org/10.1051/ijmqe/2023018/olm .
Wang, K   +2 more
core   +1 more source

Random Homoclinic Orbits

open access: yes, 1995
We introduce random homoclinic points and orbits for random dynamical systems with hyperbolic stationary orbits and investigate their meaning for irregular behaviour in form of a stochastic version of the Birkhoff-Smale Theorem.
Volker Matthias Gundlach
core  

Ruelle's Transfer Operator for Random Subshifts of Finite Type

open access: yes, 1995
We consider a Ruelle-Perron-Frobenius type of selection procedure for probability measures that are invariant under random subshifts of finite type. In particular we prove that for a class of random functions this method leads to a unique probability ...
Volker Matthias Gundlach   +1 more
core  

General Conditions for Bounded Relative Error in Simulations of Highly Reliable Markovian Systems

open access: yes, 1996
We establish a necessary condition for any importance sampling scheme to give bounded relative error when estimating a performance measure of a highly reliable Markovian system. Also, a class of importance sampling methods is defined for which we prove a
Marvin K. Nakayama, Marvin Nakayama
core  

Computable Bounds For Polynomial Ergodicity

open access: yes, 2002
This paper discusses quantitative bounds on the convergence rates of Markov chains, under conditions implying polynomial convergence rates. This paper extends an earlier work by Roberts and Tweedie [17], which provides quantitative bounds for the total ...
G. Fort, E. Moulines
core  

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