School of Mathematical Sciences

On-line parameter estimation procedures with application to estimating autoregressive parameters menu

On-line parameter estimation procedures with application to estimating autoregressive parameters

Speaker: 
Teo Sharia
Department of MathematicsRoyal Holloway, University of London
Date/Time: 
Thu, 03/06/2010 - 17:30
Room: 
M203
Seminar series: 

A wide class of on-line  estimation procedures will be proposed for the general statistical model.
In particular, new  procedures for estimating autoregressive parameters in $AR(m)$ models will be
considered. The proposed method allows for incorporation of auxiliary information into the  estimation
process, and is consistent and asymptotically efficient under certain regularity conditions. Also,
these procedures are naturally on-line and do not require storing all the data.

Two important special cases will be considered in detail: linear procedures and likelihood procedures
with the LS truncations. A specific example will also be presented to briefly discuss some practical
aspects of applications of the procedures of this type.