A Broad and General Sequential Sampling Scheme
Abstract
In this paper, we propose a broad and general sequential sampling scheme, which incorporates four different types of sampling procedures: i) the classic Anscombe-Chow-Robbins purely sequential sampling procedure; ii) the ordinary accelerated sequential sampling procedure; iii) the relatively new k-at-a-time purely sequential sampling procedure; iv) the new k-at-a-time improved accelerated sequential sampling procedure. The first-order and second-order properties of this general sequential sampling scheme are fully investigated with two illustrations on minimum risk point estimation for the mean of a normal distribution and on bounded variance point estimation for the location parameter of a negative exponential distribution, respectively. We also provide extensive computational simulation studies and real data analyses for each illustration.
Cite
@article{arxiv.2207.07283,
title = {A Broad and General Sequential Sampling Scheme},
author = {Jun Hu and Yan Zhuang},
journal= {arXiv preprint arXiv:2207.07283},
year = {2022}
}