scholarly journals The non-locality of Markov chain approximations to two-dimensional diffusions

2018 ◽  
Vol 143 ◽  
pp. 176-185 ◽  
Author(s):  
C. Reisinger
Keyword(s):  
Markov Chain ◽  
Two Dimensional ◽  
Markov Chain Approximations ◽  
Non Locality

Two-dimensional Markov Chain Simulation of Soil Type Spatial Distribution

2004 ◽  
Vol 68 (5) ◽  
pp. 1479-1490 ◽  
Author(s):  
Weidong Li ◽  
Chuanrong Zhang ◽  
James E. Burt ◽  
A.-Xing Zhu ◽  
Jan Feyen
Keyword(s):  
Spatial Distribution ◽  
Markov Chain ◽  
Soil Type ◽  
Two Dimensional

Full Two-Dimensional Markov Chain Analysis of Thermal Soft Errors in Subthreshold Nanoscale CMOS Devices

2011 ◽  
Vol 11 (1) ◽  
pp. 50-59 ◽  
Author(s):  
Pooya Jannaty ◽  
Florian Cosmin Sabou ◽  
R. Iris Bahar ◽  
Joseph Mundy ◽  
William R. Patterson ◽  
...  
Keyword(s):  
Markov Chain ◽  
Soft Errors ◽  
Two Dimensional ◽  
Markov Chain Analysis ◽  
Nanoscale Cmos ◽  
Chain Analysis

On ergodicity and recurrence properties of a Markov chain by an application to an open jackson network

1992 ◽  
Vol 24 (02) ◽  
pp. 343-376 ◽  
Author(s):  
Arie Hordijk ◽  
Flora Spieksma
Keyword(s):  
Markov Chain ◽  
Product Form ◽  
Geometric Ergodicity ◽  
Two Dimensional ◽  
Marginal Distributions ◽  
Jackson Network ◽  
Strong Ergodicity ◽  
Key Theorem ◽  
Stieltjes Transforms

This paper gives an overview of recurrence and ergodicity properties of a Markov chain. Two new notions for ergodicity and recurrence are introduced. They are calledμ-geometric ergodicity andμ-geometric recurrence respectively. The first condition generalises geometric as well as strong ergodicity. Our key theorem shows thatμ-geometric ergodicity is equivalent to weakμ-geometric recurrence. The latter condition is verified for the time-discretised two-centre open Jackson network. Hence, the corresponding two-dimensional Markov chain isμ-geometrically and geometrically ergodic, but not strongly ergodic. A consequence ofμ-geometric ergodicity withμof product-form is the convergence of the Laplace-Stieltjes transforms of the marginal distributions. Consequently all moments converge.

Analysis of a two-dimensional markov chain

1996 ◽  
Vol 25 (1) ◽  
pp. 75-79 ◽  
Author(s):  
Sharad S. Prabhu ◽  
George C. Runger
Keyword(s):  
Markov Chain ◽  
Two Dimensional
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