Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-25T09:17:29.394Z Has data issue: false hasContentIssue false

Some remarks on a One-dimensional skip-free process with repulsion

Published online by Cambridge University Press:  09 April 2009

Anthony G. Pakes
Affiliation:
Department of Mathematics, University of Western Australia, Nedlands, WA 6009, Australia
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

We extend the results obtained by Hines and Thompson for a Markov chain which has a single reflecting barrier at the origin, nearest neighbour transitions and which moves from {j} to {j + l} with probability j/(j + 1). Martingale limit theorems are used to work out an asymptotic theory for a general class of such chains for which the probability above has the form l – λ(j) = O>λ(j)>1 (j ∈N),λ(j)→ O (j →∞)and Σλ(j)=∞ We discuss the case where the last sum is finite and some alternative versions of the general case.

Type
Research Article
Copyright
Copyright © Australian Mathematical Society 1980

References

Barber, M. and Ninham, B. (1970), Random and restricted walks (Gordon and Breach, New York).Google Scholar
Bojanic, R. and Lee, Y. H., (1974), ‘An estimate for the rate of convergence of convolution products of sequences’, SIAM, J. Math. Anal. 5, 452462.CrossRefGoogle Scholar
Brown, B. M. (1971), ‘Martingale central limit theorems’, Ann. Math. Statist. 42, 5966.CrossRefGoogle Scholar
Chung, K. L. (1967), Markov chains with stationary transition Probabilities (2nd ed., Springer, Berlin).Google Scholar
Garding, L. (1961), ‘Limit theorems for certain random walks’, Math. Scand. 9, 395408.CrossRefGoogle Scholar
Harris, T. E. (1952), ‘First passage and recurrence distributions’, Trans. Amer. Math. Soc. 73, 471486.CrossRefGoogle Scholar
Heyde, C. C. and Scott, D. J. (1973), ‘Invariance principles for the law of the iterated logarithm for martingales and processes with stationary increments’, Ann. Probability 1, 428436.CrossRefGoogle Scholar
Hines, D. F. and Thompson, C. J. (1978), ‘A one-dimensional random walk with replusion’, J. Austral. Math. Soc. Ser. B 20, 375380.CrossRefGoogle Scholar
Karlin, S. and McGregor, J. (1959), ‘Random walks’, Illinois J. Math. 3, 6681.CrossRefGoogle Scholar
Lukacs, E. (1975), Stochastic convergence (2nd ed., Academic Press, New York).Google Scholar
Seneta, E. (1973), Non-negative matrices (George Allen and Unwin, London).Google Scholar
Seneta, E. (1976), Regularly varying functions, (Lecture Notes in Mathematics 508, Springer-Verlag, Berlin).CrossRefGoogle Scholar
Stout, W. (1974), Almost sure convergence (Academic Press, New York).Google Scholar
Veraverbeke, N. and Teugels, J. (1976), ‘The exponential rate of convergence of the distribution of the maximum of a random walk. Part II’, J. Appl. Probability 13, 733740.CrossRefGoogle Scholar