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Royal Holloway, University of LondonDepartment of Mathematics


 

Dr Teo Sharia

Lecturer in Statistics

at

Royal Holloway, University of London.

 



Address:

Department of Mathematics
Royal Holloway, University of London
Egham
Surrey TW20 0EX
UK
Tel
01784
414331
Email t.sharia@rhul.ac.uk


Main research interests:

Asymptotic theory of parametric estimation, recursive methods and stochastic approximation.


Selected publications:

(For a hard copy of any of these publications, just email me)

·  `The Robbins-Monro type stochastic differential equations. I. Convergence of solutions', Stochastics and Stochastic Reports, 61 (1997), 67-87 (with N. Lazrieva and T. Toronjadze).

·  `Truncated recursive estimation procedures', Proc. A. Razmadze Math. Inst. 115 (1997), 149-159.

·  `On the recursive parameter estimation for the general discrete time statistical model', Stochastic Processes Appl. 73 (1998), 2, 151-172.

·  `The Robbins-Monro type stochastic differential equations. II. Asymptotic expansion', Stochastics and Stochastics Reports, 75 (2003), 2, 153-180 (with N. Lazrieva and T. Toronjadze).

·  `Rate of convergence in recursive parameter estimation procedures' Georgian Mathematical Journal, 14 (2007), 761-776.

·  `Parameter Estimation Procedures in Time Series Models', Inference and Estimation in Probabilistic Time-Series Models , Isaac Newton Institute for Mathematical Sciences, Cambridge UK (2008), 57-66.

·  `Semimartingale Stochastic Approximation Procedures', Journal of Mathematical Sciences , 153 (2008), 3, pp. 211 -- 261 (with N. Lazrieva and T. Toronjadze). (pdf)

·  `Recursive parameter estimation: Convergence' Statistical Inference for Stochastic Processes, , 11 (2008), 2, 157 - 175.

·  `Recursive parameter estimation: Asymptotic expansion', Annals of the Institute of Statistical Mathematics ,  62 (2010), 2, 343-236. (pdf) .

·  `New Efficient Estimation Procedures in Autoregressive Time Series Models', Mathematical Methods of Statistics , (2010) (to appear) (pdf)

·  `On parameter estimation in partially observable Markov chain models' (in preparation)


T. Sharia