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A reversibility relationship for two Markovian time series models by stationary exponential tailed distribution
Part of
- Markov processes
- Inference from stochastic processes
R. P. Littlejohn
Journal:

Journal of Applied Probability / Volume 31 / Issue 2 / June 1994

Published online by Cambridge University Press:

14 July 2016, pp. 575-581

Print publication:

June 1994
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The continuous autoregressive and minification stationary non-negative time series models discussed by Chernick et al. (1988) are generalized to model marginal distributions which have atoms of mass at zero. The reversibility theorem relating these processes with exponential marginal distributions is extended to the case where the marginal distribution has exponential tail.

Discrete minification processes and reversibility
Part of
- Markov processes
- Inference from stochastic processes
R. P. Littlejohn
Journal:

Journal of Applied Probability / Volume 29 / Issue 1 / March 1992

Published online by Cambridge University Press:

14 July 2016, pp. 82-91

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March 1992
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Discrete minification processes are introduced and it is proved that the discrete first-order autoregression of McKenzie (1986) and the discrete minification process are mutually time-reversible if and only if they have common marginal geometric distribution, corresponding to a result for continuous processes given by Chernick et al. (1988). It is also proved that a discrete minification process is time-reversible if and only if it has marginal Bernoulli distribution.

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2 results

A reversibility relationship for two Markovian time series models by stationary exponential tailed distribution

Discrete minification processes and reversibility