hi, i am intersted in obtaining the paper for teh seminar. Can you please
let me know how I can get it?
Thanks,
Robert
Professor Robert Kohn
612 9931 9265 (Voice)
612 9662 7621 (Fax)
email:
[log in to unmask]
On Thu, 27 Jan 2000, Kostas Skouras wrote:
> ************** Please note change of address *********************
> ***** Our department has moved to new premises. ***************
> ***** A map with instructions on how to get to our **************
> ***** department can be found at the following web site: *********
> ***** http://www.ucl.ac.uk/Stats/map.html ************************
>
> Everyone is welcome. Tea, coffee and biscuits are provided!
>
> Details of the seminar:
> ================
>
> Monday 31 January 2000 - 4pm, Room 102, 1-19 Torrington Place,
> Department of Statistical Science - University College London.
>
> Speaker : Dr V. A. Hadjivassiliou
>
> Title: Some Practical Issues in Maximum Simulated Likelihood
>
> Abstract: In this paper I explore ways of recapturing the efficiency
> property for
> estimators that rely on simulation. In particular, I show that this can be
> achieved by exploiting two-step maximum simulated likelihood (MSL) estimation
> methods that are familiar from classical applications. I also construct
> a diagnostic test for adequacy of number of simulations employed to
> guarantee negligible bias for the MSL and provide some evidence on the
> computational requirements of the Geweke-Hajivassiliou-Keane (GHK)
> simulator as a function of (a) the dimension of the problem and (b) the
> number of simulations employed in a vectorized context. I outline how one
> can derive a similar approach for checking the adequacy of the number of
> Gibbs resamplings in simulation estimation methods that employ this technique.
>
> This paper also shows how to suitably introduce simulation into classical
> hypothesis testing methods and provide test statistics (simulated Wald,
> Lagrange Multiplier, and Likelihood Ratio Tests) that are free of
> influential simulation noise.
>
> Finally, I explain how simulation-variance-reduction techniques, notably
> antithetics, can improve substantially the practical performance of the GHK
> simulator and present extensive Monte-Carlo evidence confirming this.
>
> ----------------------------------------------------------------------------
> ----------
> K. Skouras, Lecturer in Statistics, Department of Statistical Science, UCL,
> 1-19 Torringhton Place, London WC1E 6BT, United Kingdom.
> Tel: 020 - 76791862 Fax: 0171-7383 4703
> e-mail: [log in to unmask]
> ----------------------------------------------------------------------------
> -----------
>
>
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|