Conditional and Restricted Pareto Sampling: Two New Methods for Unequal Probability Sampling
提出了两种新的不等概率抽样方法：条件帕累托抽样和受限帕累托抽样。前者比标准帕累托抽样更准确地实现目标包含概率，后者能处理样本有多个限制的情况，是平衡抽样中立方方法的替代方案。
Abstract. Two new unequal probability sampling methods are introduced: conditional and restricted Pareto sampling. The advantage of conditional Pareto sampling compared with standard Pareto sampling, introduced by Rosén (J. Statist. Plann. Inference, 62, 1997, 135, 159), is that the factual inclusion probabilities better agree with the desired ones. Restricted Pareto sampling, preferably conditioned or adjusted, is able to handle cases where there are several restrictions on the sample and is an alternative to the recent cube method for balanced sampling introduced by Deville and Tillé (Biometrika, 91, 2004, 893). The new sampling designs have high entropy and the involved random numbers can be seen as permanent random numbers.