Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-30T23:18:39.388Z Has data issue: false hasContentIssue false
  • English
  • Français

Self-avoiding walks

Published online by Cambridge University Press:  01 July 2016

J. M. Hammersley
J. M. Hammersley*
Affiliation:
University of Oxford
Get access Rights & Permissions [Opens in a new window]

Abstract

An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
I. Invited Review and Research Papers
Information
Advances in Applied Probability , Volume 7 , Issue 2 , June 1975 , pp. 234
Copyright
Copyright © Applied Probability Trust 1975 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

[1] Billingsley, P. (1961) Statistical Inference for Markov Processes. University of Chicago Press, Chicago.Google Scholar
[2] Brown, B. M. (1971) Martingale central limit theorems. Ann. Math. Statist. 42, 59–66.CrossRefGoogle Scholar
[3] Hannan, E. J. and Heyde, C. C. (1972) On limit theorems for quadratic functions of discrete time series. Ann. Math. Statist. 43, 2058–2066.CrossRefGoogle Scholar
[4] Heyde, C. C. (1972) Martingales: a case for a place in the Statistician's repertoire. Austral. J. Statist. 14, 1–9.CrossRefGoogle Scholar
[5] Heyde, C. C. (1973) An iterated logarithm result for martingales and its application in estimation theory for autoregressive processes. J. Appl. Prob. 10, 146–157.CrossRefGoogle Scholar
[6] Heyde, C. C. (1974) On estimating the variance of the offspring distribution in a simple branching process. Adv. Appl. Prob. 6, 421–433.CrossRefGoogle Scholar
[7] Heyde, C. C. (1974) On martingale limit theory and strong convergence results for stochastic approximation procedures. Stochastic Processes Appl. 2, 359–370.CrossRefGoogle Scholar
[8] Heyde, C. C. and Seneta, E. (1972) Estimation theory for growth and immigration rates in a multiplicative process. J. Appl. Prob. 9, 235–256.CrossRefGoogle Scholar
[9] Neveu, J. (1970) Calcul des Probabilités 2nd ed. Masson et Cie, Paris.Google Scholar
[10] Rao, C. R. (1965) Linear Statistical Inference and its Applications. Wiley, New York.Google Scholar
[11] Roussas, G. G. (1972) Contiguity of Probability Measures. Cambridge University Press, Cambridge.CrossRefGoogle Scholar