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Rescaling bootstrap variance estimation technique under dual frame surveys with unknown domain sizes

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Title Rescaling bootstrap variance estimation technique under dual frame surveys with unknown domain sizes
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Creator Rajeev Kumar
Anil Rai
Tauqueer Ahmad
Ankur Biswas
P.M. Sahoo
P.K. Moury
 
Subject Domain estimation
Dual frame surveys
Rescaling bootstrap
Rescaling factor
 
Description Not Available
Dual frame (DF) surveys are a special case of multiple frame (MF) surveys considering two frames covering the entire population. Dual frame surveys are applicable in those situations, where, one frame may cover the entire population but is very expensive to sample; so an alternate frame may be available that does not cover the entire population but is easily available. Unbiased variance estimation in dual frame surveys can be difficult and complicated than corresponding estimators under single frame surveys. Again, the variance of dual frame estimator involves population variances of the individual domains which are generally unknown. Due to this reason, obtaining an unbiased estimate of the variance of the dual frame estimator is quite complex in the case of dual frame surveys. In this article, we propose a Post-stratified Rescaling Bootstrap with Unknown Domain size (PstRBUD) method for variance estimation of the dual frame estimator of population total. The proposed rescaled bootstrap method was compared to that of standard bootstrap methods in simulation analysis. The proposed PstRBUD method provides an unbiased estimation of the variance of the dual frame estimator of population total, according to simulation results.
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Date 2024-05-14T10:24:21Z
2024-05-14T10:24:21Z
2024-02-22
 
Type Journal
 
Identifier Kumar, R., Rai, A., Ahmad, T., Biswas, A., Sahoo, P.M. and Moury, P.K. (2024). Rescaling bootstrap variance estimation technique under dual frame surveys with unknown domain sizes. Communications in Statistics - Simulation and Computation, DOI: 10.1080/03610918.2024.2314671
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http://krishi.icar.gov.in/jspui/handle/123456789/82821
 
Language English
 
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Publisher Not Available