Mathematics – Statistics Theory
Scientific paper
2011-09-29
Mathematics
Statistics Theory
arXiv admin note: substantial text overlap with arXiv:1105.5036
Scientific paper
The paper considers the problem of estimating the parameters in a continuous time regression model with a non-Gaussian noise of pulse type. The noise is specified by the Ornstein-Uhlenbeck process driven by the mixture of a Brownian motion and a compound Poisson process. Improved estimates for the unknown regression parameters, based on a special modification of the James-Stein procedure with smaller quadratic risk than the usual least squares estimates, are proposed. The developed estimation scheme is applied for the improved parameter estimation in the discrete time regression with the autoregressive noise depending on unknown nuisance parameters.
No associations
LandOfFree
Improved estimation in a non-Gaussian parametric regression does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Improved estimation in a non-Gaussian parametric regression, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Improved estimation in a non-Gaussian parametric regression will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-151805