Grafström, Anton and Qualité, Lionel and Tillé, Yves and Matei, Alina
(2012).
Size constrained unequal probability sampling with a noninteger sum of inclusion probabilities.
Electronic journal of statistics. 6, 14771489
[Journal article]

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Official URL: http://dx.doi.org/10.1214/12EJS719
Abstract
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.
Authors/Creators:  Grafström, Anton and Qualité, Lionel and Tillé, Yves and Matei, Alina  

Title:  Size constrained unequal probability sampling with a noninteger sum of inclusion probabilities  
Series/Journal:  Electronic journal of statistics (19357524)  
Year of publishing :  2012  
Volume:  6  
Page range:  14771489  
Publisher:  Institute of Mathematical Statistics, Bernoulli Society for Mathematical Statistics and Probability  
ISSN:  19357524  
Language:  English  
Publication Type:  Journal article  
Refereed:  Yes  
Article category:  Scientific peer reviewed  
Version:  Published version  
Full Text Status:  Public  
Agris subject categories.:  U Auxiliary disciplines > U10 Mathematical and statistical methods X Agricola extesions > X10 Mathematics and statistics  
Subjects:  (A) Swedish standard research categories 2011 > 1 Natural sciences > 101 Mathematics > 10106 Probability Theory and Statistics  
Keywords:  survey sampling, maximum entropy, splitting method  
URN:NBN:  urn:nbn:se:slu:epsilone776  
Permanent URL:  http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilone776  
Additional ID: 
 
ID Code:  9317  
Department:  (S) > Dept. of Forest Resource Management (NL, NJ) > Dept. of Forest Resource Management  
Deposited By:  Skogsbiblioteket Umeå  
Deposited On:  13 Dec 2012 11:28  
Metadata Last Modified:  02 Dec 2014 10:53 
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