Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-27T17:58:10.621Z Has data issue: false hasContentIssue false
  • English
  • Français

THE ET INTERVIEW: B.L.S. PRAKASA RAO

Part of: ET Interviews

Published online by Cambridge University Press:  27 September 2010

Arup Bose
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
Other
Information
Econometric Theory , Volume 27 , Issue 2 , April 2011 , pp. 373 - 411
Copyright
Copyright © Cambridge University Press 2011

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

REFERENCES

Basawa, I.V. & Scott, D.J. (1983) Asymptotic Optimal Inference for Non-ergodic Models. Lecture Notes in Statistics 17. Springer-Verlag.CrossRefGoogle Scholar
Bhat, B.R. (1974) On the method of maximum-likelihood for dependent observations. Journal of the Royal Statistical Society, Series B 36, 48–53.Google Scholar
Billingsley, P. (1961) Statistical Inference for Markov Processes. University of Chicago Press.Google Scholar
Bose, Arup (1983a) Asymptotic theory of estimation in non-linear stochastic differential equations for the multiparameter case. Sankhyā, Series A 45, 56–65.Google Scholar
Bose, Arup (1983b) The Bernstein-von Mises theorem for a certain class of diffusion processes. Sankhyā, Series A 45, 150–160.Google Scholar
Chakravarti, I.M., Laha, R.G., & Roy, J. (1967) Handbook of Methods of Applied Statistics, vol. 1. Wiley.Google Scholar
Chernoff, H. (1964) Estimation of the mode. Annals of the Institute of Statistical Mathematics 16, 31–41.CrossRefGoogle Scholar
Ibragimov, I.A. & Khasminski, R.Z. (1981) Statistical Estimation: Asymptotic Theory. Springer-Verlag.CrossRefGoogle Scholar
Jeganathan, P. (1982) On the asymptotic theory of estimation when the limit of the log-likelihood ratio is mixed normal. Sankhyā 44, 173–212.Google Scholar
Kallianpur, G. & Rao, C.R. (1955) On Fisher’s lower bound to asymptotic variance of a consistent estimat. Sankhyā 16, 331–342.Google Scholar
Le Cam, L. & Yang, C.L. (2000) Asymptotics in Statistics: Some Basic Concepts, 2nd ed. Springer-Verlag.CrossRefGoogle Scholar
Parzen, E. (1954) On uniform convergence of families of sequences of random variables. University of California Publications in Statistics 2, pp. 23–53.Google Scholar
Prakasa Rao, B.L.S. & Sen, Arusharka (1995a) An application of the “martingale methods” to nonparametric regression based on censored data. Statistics & Decisions 13, 201–220.Google Scholar
Prakasa Rao, B.L.S. & Sen, Arusharka (1995b) Limit distributions of conditional U-statistics. Journal of Theoretical Probability 8, 261–301.CrossRefGoogle Scholar
Prasad, M.S. & Prakasa Rao, B.L.S. (1976) Maximum likelihood estimation for dependent random variables. Journal of the Indian Statistical Association 14, 75–97.Google Scholar
Rao, C.R., Mitra, S.K., & Matthai, A. (1996) Formulae and Tables for Statistical Work. Calcutta Statistical Publishing Society.Google Scholar
Roussas, G.G. (1991) Kernel estimates under association: Strong uniform consistency. Statistics and Probability Letters 12, 393–403.CrossRefGoogle Scholar
Roussas, G.G. (2008) On conditional independence, mixing and association, Stochastic Analysis and Applications 26, 1274–1309.CrossRefGoogle Scholar