A note on random time changes of Markov chains

1984 ◽  
Vol 1984 (2) ◽  
pp. 127-129 ◽  
Author(s):  
D. Pfeifer
Keyword(s):  
Markov Chains ◽  
Random Time ◽  
Time Changes

Approximating Transition Probabilities and Mean Occupation Times in Continuous-Time Markov Chains

1987 ◽  
Vol 1 (3) ◽  
pp. 251-264 ◽  
Author(s):  
Sheldon M. Ross
Keyword(s):  
Markov Chains ◽  
Continuous Time ◽  
Transition Probabilities ◽  
Random Time ◽  
Occupation Times ◽  
New Approach ◽  
Continuous Time Markov Chains ◽  
The Mean ◽  
Mean Time

In this paper we propose a new approach for estimating the transition probabilities and mean occupation times of continuous-time Markov chains. Our approach is to approximate the probability of being in a state (or the mean time already spent in a state) at time t by the probability of being in that state (or the mean time already spent in that state) at a random time that is gamma distributed with mean t.

scholarly journals Subgeometric Ergodicity Analysis of Continuous-Time Markov Chains under Random-Time State-Dependent Lyapunov Drift Conditions

2014 ◽  
Vol 2014 ◽  
pp. 1-5
Author(s):  
Mokaedi V. Lekgari
Keyword(s):  
Markov Chains ◽  
Discrete Time ◽  
Continuous Time ◽  
Random Time ◽  
Lyapunov Analysis ◽  
Continuous Time Markov Chains ◽  
State Dependent ◽  
Drift Conditions

We investigate random-time state-dependent Foster-Lyapunov analysis on subgeometric rate ergodicity of continuous-time Markov chains (CTMCs). We are mainly concerned with making use of the available results on deterministic state-dependent drift conditions for CTMCs and on random-time state-dependent drift conditions for discrete-time Markov chains and transferring them to CTMCs.

scholarly journals Random Times for Markov Processes with Killing

2021 ◽  
Vol 5 (4) ◽  
pp. 254
Author(s):  
Yuri G. Kondratiev ◽  
José Luís da Silva
Keyword(s):  
Markov Processes ◽  
Schrödinger Operators ◽  
Random Time ◽  
Schrodinger Operators ◽  
Time Behavior ◽  
Non Local ◽  
Time Changes ◽  
Random Times

We consider random time changes in Markov processes with killing potentials. We study how random time changes may be introduced in these Markov processes with killing potential and how these changes may influence their time behavior. As applications, we study the parabolic Anderson problem, the non-local Schrödinger operators as well as the generalized Anderson problem.

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