Asymptotically optimum estimation of a probability in inverse binomial sampling

Details Asymptotically optimum estimation of a probability in inverse binomial sampling Asymptotically optimum estimation of a probability in inverse binomial sampling

2010-01-18

arxiv.org/abs/1001.3084v2

Mathematics

Statistics Theory

Scientific paper

The optimum quality that can be asymptotically achieved in the estimation of a probability p using inverse binomial sampling is considered in this paper. A general definition of quality is used, in terms of the risk associated with a loss function that satisfies certain assumptions. It is shown that the limit superior of the risk for p asymptotically small has a minimum over all (possibly randomized) estimators. This minimum is achieved by certain non-randomized estimators. The model includes commonly used quality criteria as particular cases. Applications to the non-asymptotic regime for specific loss functions are discussed.

Affiliated with

Also associated with

No associations

Rating

Asymptotically optimum estimation of a probability in inverse binomial sampling 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 Asymptotically optimum estimation of a probability in inverse binomial sampling, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Asymptotically optimum estimation of a probability in inverse binomial sampling will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-661392