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Size constrained unequal probability sampling with a non-integer sum of inclusion probabilities

Auteur(s)
Grafström, A.
Qualité, Lionel 
Institut de statistique 
Tillé, Yves 
Institut de statistique 
Matei, Alina 
Institut de statistique 
Date de parution
2012
In
Electronic Journal of Statistics
No
6
De la page
1477
A la page
1489
Revu par les pairs
1
Résumé
More than 50 methods have been developed to draw unequal probability samples with fixed sample size. All these methods require the sum of the inclusion probabilities to be an integer number. There are cases, however, where the sum of desired inclusion probabilities is not an integer. Then, classical algorithms for drawing samples cannot be directly applied. We present two methods to overcome the problem of sample selection with unequal inclusion probabilities when their sum is not an integer and the sample size cannot be fixed. The first one consists in splitting the inclusion probability vector. The second method is based on extending the population with a phantom unit. For both methods the sample size is almost fixed, and equal to the integer part of the sum of the inclusion probabilities or this integer plus one.
Identifiants
https://libra.unine.ch/handle/123456789/15099
Autre version
http://projecteuclid.org/DPubS?verb=Display&version=1.0&service=UI&handle=euclid.ejs/1346421601&page=record
Type de publication
journal article
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