Sampling and Estimation from Finite Populations. Yves Tille

Sampling and Estimation from Finite Populations - Yves Tille


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      Result 2.5

      The variance of the expansion estimator of the total is

      Proof:

equation

      It is also possible to write the expansion estimator with a vector notation. Let images be the vector of dilated values:

equation equation

      The calculation of the variance is then immediate:

equation

      If the sample is of fixed sample size, Sen (1953) and Yates & Grundy (1953) have shown the following result:

      Result 2.6

      If the sampling design is of fixed sample size, then the variance of the expansion estimator can also be written as

      Proof:

      Under a design with fixed sample size, it has been proved in Result 2.2, page 16, that

equation

      The first two terms of Expression (2.5) are therefore null and we find the expression of Result 2.5.

      In order to estimate the variance, we use the following general result:

      Result 2.7

      Let images be a function from images to images. A necessary and sufficient condition for

equation

      to unbiased ly estimate

equation

      is that images for all images

      Proof:

      Since

equation

      the estimator is unbiased if and only if images for all images

      (2.6)equation

      This estimator can take negative values, but is unbiased.

      The second one is called Sen–Yates–Grundy estimator (see Sen, 1953; Yates & Grundy, 1953). It is unbiased only for designs with fixed sample size s. It is obtained by applying Result 2.7 to Expression (2.4):

      (2.7)equation

      This estimator can also take negative values, but when images for all images then the estimator is always positive. This condition is called the Yates–Grundy condition.

      The Yates–Grundy condition is a special case of the negative correlation property defined as follows:

      Definition 2.8

      A sampling design is said to be negatively correlated if, for all images

equation

      

      Sampling designs with replacement should not be used except in very special cases, such as in indirect sampling, described in Section 8.4, page 187 (Deville & Lavallée, 2006; Lavallée, 2007), adaptive sampling, described in Section 8.4.2, page 188 (Thompson, 1988), or capture–recapture techniques, also called capture–mark sampling, described in Section 8.5, page 191 (Pollock, 1981; Amstrup et al., 2005).

      In a sampling design with replacement, the same unit can be selected several times in the sample. The random sample can be written using a vector images, where images represents the number of times that unit images is selected in the sample. The images can therefore take any non‐negative integer value.


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