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Lumpability : ウィキペディア英語版
Lumpability
In probability theory, lumpability is a method for reducing the size of the state space of some continuous-time Markov chains, first published by Kemeny and Snell.〔

==Definition==
Suppose that the complete state-space of a Markov chain is divided into disjoint subsets of states, where these subsets are denoted by ''ti''. This forms a partition \scriptstyle is lumpable with respect to the partition ''T'' if and only if, for any subsets ''ti'' and ''tj'' in the partition, and for any states ''n,n’'' in subset ''ti'',
: \sum_ q(n,m) = \sum_ q(n',m) ,
where ''q''(''i,j'') is the transition rate from state ''i'' to state ''j''.〔Jane Hillston, (''Compositional Markovian Modelling Using A Process Algebra'' ) in the Proceedings of the Second International Workshop on Numerical Solution of Markov Chains: Computations with Markov Chains, Raleigh, North Carolina, January 1995. Kluwer Academic Press〕
Similarly, for a stochastic matrix ''P'', ''P'' is a lumpable matrix on a partition ''T'' if and only if, for any subsets ''ti'' and ''tj'' in the partition, and for any states ''n,n’'' in subset ''ti'',
: \sum_ p(n,m) = \sum_ p(n',m) ,
where ''p''(''i,j'') is the probability of moving from state ''i'' to state ''j''.〔Peter G. Harrison and Naresh M. Patel, ''Performance Modelling of Communication Networks and Computer Architectures'' Addison-Wesley 1992〕

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