The Gaussian approximation for multi-color generalized Friedman's urn model

Mathematics – Probability

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

10.1007/s11425-009-0092-9

The Friedman's urn model is a popular urn model which is widely used in many disciplines. In particular, it is extensively used in treatment allocation schemes in clinical trials. In this paper, we prove that both the urn composition process and the allocation proportion process can be approximated by a multi-dimensional Gaussian process almost surely for a multi-color generalized Friedman's urn model with non-homogeneous generating matrices. The Gaussian process is a solution of a stochastic differential equation. This Gaussian approximation together with the properties of the Gaussian process is important for the understanding of the behavior of the urn process and is also useful for statistical inferences. As an application, we obtain the asymptotic properties including the asymptotic normality and the law of the iterated logarithm for a multi-color generalized Friedman's urn model as well as the randomized-play-the-winner rule as a special case.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

The Gaussian approximation for multi-color generalized Friedman's urn model 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 The Gaussian approximation for multi-color generalized Friedman's urn model, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and The Gaussian approximation for multi-color generalized Friedman's urn model will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-726645

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.