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Inference from non-ergodic time series

Published online by Cambridge University Press:  01 July 2016

R. B. Davies
R. B. Davies*
Affiliation:
Applied Mathematics Division, DSIR, Wellington
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Abstract

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Type
Eighth Conference on Stochastic Processes and their Applications
Information
Advances in Applied Probability , Volume 11 , Issue 2 , June 1979 , pp. 261 - 262
Copyright
Copyright © Applied Probability Trust 1979 

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References

Basawa, I. V. and Scott, D. J. (1976) Efficient tests for branching processes. Biometrika 63, 531–536.CrossRefGoogle Scholar
Feigin, P. D. (1978) The efficiency criteria problem for stochastic processes. Stoch. Proc. Appl. 6, 115–127.Google Scholar
Heyde, C. C. (1975) Remarks on efficiency in estimation for branching processes. Biometrika 62, 49–55.Google Scholar
Heyde, C. C. (1977) An optimal property of maximum likelihood with an application to branching process estimation. Bull. Internat. Statist. Inst. 47.Google Scholar
Heyde, C. C. and Feigin, P. D. (1975) On efficiency and exponential families in stochastic process estimation. In Statistical Distribution in Scientific Work, Vol. 1. ed. Patil, G. P. et al., Reidel, Dordrecht, 227–240 Google Scholar
Le Cam, L. (1969) Théorie Asymptotique de la Décision Statistique. University of Montreal Press.Google Scholar