@MISC{Rubin04estimationof, author = {A. Dasgupta Herman Rubin}, title = {Estimation of Binomial Parameters when Both n, p are Unknown}, year = {2004} }
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Abstract
We revisit the classic problem of estimation of the binomial parameters when both parameters n, p are unknown. We start with a series of results that illustrate the fundamental difficulties in the problem. Specifically, we establish lack of unbiased estimates for essentially any functions of just n or just p. We also quantify just how badly biased the sample maximum is as an estimator of n. Then we motivate and present two new estimators of n. One is a new moment estimate and the other is a bias correction of the sample maximum. Both are easy to motivate, compute, and jackknife. The second estimate frequently beats most common estimates of n in the simulations, including the Carroll-Lombard estimate. This estimate is very promising. We end with a family of estimates for p; a specific one from the family is compared to the presently common estimate max{1 − s2,