Subgeometric rates of convergence for Markov processes under subordination
2017 ◽
Vol 49
(1)
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pp. 162-181
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Keyword(s):
Abstract We are interested in the rate of convergence of a subordinate Markov process to its invariant measure. Given a subordinator and the corresponding Bernstein function (Laplace exponent), we characterize the convergence rate of the subordinate Markov process; the key ingredients are the rate of convergence of the original process and the (inverse of the) Bernstein function. At a technical level, the crucial point is to bound three types of moment (subexponential, algebraic, and logarithmic) for subordinators as time t tends to ∞. We also discuss some concrete models and we show that subordination can dramatically change the speed of convergence to equilibrium.
2002 ◽
Vol 39
(1)
◽
pp. 123-136
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2002 ◽
Vol 39
(01)
◽
pp. 123-136
◽
2017 ◽
Vol 53
(2)
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pp. 503-538
1983 ◽
Vol 15
(01)
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pp. 54-80
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2002 ◽
Vol 39
(1)
◽
pp. 137-160
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2001 ◽
Vol 45
(3)
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pp. 466-479
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