5330
2015
eng
483
499
3
22
article
0
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Computing the nearest reversible Markov chain
Reversible Markov chains are the basis of many applications. However, computing transition probabilities by a finite sampling of a Markov chain can lead to truncation errors. Even if the original Markov chain is reversible, the approximated Markov chain might be non-reversible and will lose important properties, like the real valued spectrum. In this paper, we show how to find the closest reversible Markov chain to a given transition matrix. It turns out that this matrix can be computed by solving a convex minimization problem.
Numerical Linear Algebra with Applications
10.1002/nla.1967
yes
urn:nbn:de:0297-zib-53292
Adam Nielsen
Adam Nielsen
Marcus Weber
eng
uncontrolled
Reversible Markov Chain
deu
uncontrolled
Convex Optimization
deu
uncontrolled
MSM
LINEAR AND MULTILINEAR ALGEBRA; MATRIX THEORY
COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area)
Numerical Mathematics
Computational Molecular Design
Weber, Marcus
BMS-Nielsen
EyeTracking
NonequiMSM
SFB1114-A5