@misc{NielsenWeber, author = {Nielsen, Adam and Weber, Marcus}, title = {Computing the nearest reversible Markov chain}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-53292}, abstract = {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.}, language = {en} } @article{NielsenWeber, author = {Nielsen, Adam and Weber, Marcus}, title = {Computing the nearest reversible Markov chain}, series = {Numerical Linear Algebra with Applications}, volume = {22}, journal = {Numerical Linear Algebra with Applications}, number = {3}, doi = {10.1002/nla.1967}, pages = {483 -- 499}, abstract = {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.}, language = {en} }