This paper reports a simulation-based exploration into the computation of point and interval estimates for data arising from sequential sampling. We conclude that the coverage probability of the standard frequentist confidence interval estimates is overstated. However, there are other interval estimates which do not overstate the coverage probability if the underlying population is Gaussian. Futher, the effect of non-Gaussian behavior in the underlying population upon the properties of the interval estimate varies, depending upon the severity and the flavor, that is, whether it is skewness, kurtosis, etc.
Research supported by the College of Natural Resources and the Minnesota Agricultural Experiment Station, University of Minnesota, St. Paul, the McIntire-Stennis Cooperative Forestry Research Program and the USDA Small Business Innovation Research Program. Published as MAES paper no. 974420122 of the Minnesota Agricultural Experiment Station.
Robinson, Andrew P.; Burk, Thomas E..
Point and interval estimates from sequential sampling..
University of Minnesota.
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