Synthetic Estimators Using Auxiliary Information in Small Domains - Kant Rai, Piyush
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An unbiased estimate is obtained from a sample survey for a large area; when this estimate is used to derive estimates for sub areas on the assumption that the small areas have the same characteristics as larger area, we identify these estimates as synthetic estimators". One of the simplest estimators arises from the assumption that the small area mean is equal to the larger area mean. This leads to the simple synthetic estimator under simple random sampling or stratified random sampling or post stratified sampling as the case may be. Synthetic estimation may also be based on auxiliary data.…mehr

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Produktbeschreibung
An unbiased estimate is obtained from a sample survey for a large area; when this estimate is used to derive estimates for sub areas on the assumption that the small areas have the same characteristics as larger area, we identify these estimates as synthetic estimators". One of the simplest estimators arises from the assumption that the small area mean is equal to the larger area mean. This leads to the simple synthetic estimator under simple random sampling or stratified random sampling or post stratified sampling as the case may be. Synthetic estimation may also be based on auxiliary data. Such estimators are, for example, ratio-synthetic, product -synthetic and regression - synthetic estimators.
Autorenporträt
Dr. Piyush Kant Rai is Associate Professor of Statistics at Banasthali University. He did his M.Sc.from BHU with Gold Medal and Ph.D. from Banasthali. Dr. Rai has published more than 20 research articles of various Journals of international repute. He has collaboration with various societies like ASI,IBS,ISBA,SSCA and other organizations.