We develop two methods for obtaining a confidence band for the cumulative distribution function (CDF) based on a simple random sample from a finite population of known size. The methods are exact when the population contains no repeated values, and conservative otherwise. The first method...

We consider the problem of estimating the variance of a population using judgment post-stratification. By conditioning on the observed vector of ordered in-stratum sample sizes, we develop a conditionally unbiased nonparametric estimator that outperforms the sample variance except when the...

Standard nonparametric prediction intervals for a future order statistic are obtained by taking the interval between two order statistics of the initial sample. We obtain improved prediction intervals by taking the shortest of two or more standard intervals.

We consider the problem of testing for perfect rankings in ranked set sampling (RSS). By using a new algorithm for computing the probability that specified independent random variables have a particular ordering, we find most powerful rank tests of the null hypothesis of perfect rankings against...

We prove that the standard nonparametric mean estimator for judgment post-stratification is inadmissible under squared error loss within a certain class of linear estimators. We derive alternate estimators that are admissible in this class, and we show that one of them is always better than the...

If posterior means are used to estimate nonlinear functionals of an ensemble of parameters, biased estimates of those functionals typically result. Posterior means are optimal under sum-of-squared-error loss (SSEL); introducing weighting and at the same time discarding SSEL optimality may lead...