Sequential Poisson Sampling
Sequential Poisson Sampling
复制标题
顺序泊松采样
DOI：
--
复制
发表时间：
1999
期刊：
影响因子：
--
通讯作者：
EsbjoÈrn Ohlsson
中科院分区：
文献类型：
--
作者：
EsbjoÈrn Ohlsson
其中i [ s]表示单元i包括在样本s中，并且n是期望的样本大小。Sigman和Monsour（1995）注意到在商业调查中使用pps抽样，特别是在价格指数估计中。在这种应用中，n通常具有中等或大的尺寸，参见，Dalen and Ohlsson（1995）.这与多阶段调查中pps抽样的情况相反，在多阶段调查中，n为1或2是常见的。泊松抽样是一种简单的方法，可以从一个夜间人口中抽取与大小成比例的概率（pps）样本。它还提供了一种简单的方法来更新样本，同时保留尽可能多的单位，从以前的样本，和/或最大限度地减少不同样本的重叠。泊松抽样的一个缺点是随机样本大小。我们提出了一种固定大小的泊松抽样，顺序泊松抽样，设计，并用于，瑞典消费者价格指数（CPI）。我们证明了与普通和序贯泊松抽样相关的相应估计量都是渐近正态分布和无偏的，并且同样有效。对CPI数据的模拟验证了方差的近似无偏性和近似相等性，以及相关方差估计的同样良好的性能。因此，由于固定的大小，顺序泊松采样是优选的。
where i [ s denotes that unit i is included in the sample s, and n is the desired sample size. Sigman and Monsour (1995) note the use of pps sampling for business surveys, especially for price index estimation. In this kind of application, n is typically of moderate or large size, cf., DaleÂn and Ohlsson (1995). This is in contrast to the case with pps sampling in multi-stage surveys, where n 1 or 2 is common. Poisson sampling is a simple way to draw a probability proportional to size (pps) sample from a ®nite population. It also offers an easy way to update a sample while retaining as many units as possible from the previous sample, and/or to minimize overlap of different samples. A drawback of Poisson sampling is the random sample size. We present a ®xed size alteration of Poisson sampling, sequential Poisson sampling, designed for, and used in, the Swedish Consumer Price Index (CPI). We show that the respective estimators associated with ordinary and sequential Poisson sampling, are both asymptotically normally distributed and unbiased as well as equally ef®cient. Simulations on CPI data verify approximate unbiasedness and approximate equality of variances, plus equally good performance of associated estimators of variance. Therefore, sequential Poisson sampling is preferable, because of the ®xed size.