When a sample is taken from a population additionally for a certain of its components called domains also estimates are needed for certain parameters. When domain-wise samples are too small these estimates turn out poor in efficiency. By borrowing strength from other domains how data may be appropriately used is an important issue. How to settle this using domain as well as past data is a story related in this monograph. For this appropriate model-assisted analysis is described in details. Historical developments are narrated and live data-base emperical findings are presented in great details. Mainly the author's own research in collaboration with his students and colleagues is stressed. Contemporary research by others is also touched to the extent possible in this short output. Further a point of interest is to start with classical estimation methods based on unequal probability sampling and to follow up with appropriate modelling. This has been diligently implemented as is not usually emphasised in the current literature on Small Area Estimation.
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When a sample is taken from a population additionally for a certain of its components called domains also estimates are needed for certain parameters. When domain-wise samples are too small these estimates turn out poor in efficiency. By borrowing strength from other domains how data may be appropriately used is an important issue. How to settle this using domain as well as past data is a story related in this monograph. For this appropriate model-assisted analysis is described in details. Historical developments are narrated and live data-base emperical findings are presented in great details. Mainly the author's own research in collaboration with his students and colleagues is stressed. Contemporary research by others is also touched to the extent possible in this short output. Further a point of interest is to start with classical estimation methods based on unequal probability sampling and to follow up with appropriate modelling. This has been diligently implemented as is not usually emphasised in the current literature on Small Area Estimation.
Now an honorary visiting professor in Indian Statistical Institute since o1 September, 2005 after serving as a professor and on retirement on 31 August, 2002 and a CSIR emeritus scientist for 3 years in ISI thereafter. Published about 150 papers in peer-reviewed journals, a few jointly with students and colleagues. Also published six monographs.
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Librería: moluna, Greven, Alemania
Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Chaudhuri ArijitNow an honorary visiting professor in Indian Statistical Institute since o1 September, 2005 after serving as a professor and on retirement on 31 August, 2002 and a CSIR emeritus scientist for 3 years in ISI thereafter. Nº de ref. del artículo: 5134101
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - When a sample is taken from a population additionally for a certain of its components called domains also estimates are needed for certain parameters. When domain-wise samples are too small these estimates turn out poor in efficiency. By borrowing strength from other domains how data may be appropriately used is an important issue. How to settle this using domain as well as past data is a story related in this monograph. For this appropriate model-assisted analysis is described in details. Historical developments are narrated and live data-base emperical findings are presented in great details. Mainly the author's own research in collaboration with his students and colleagues is stressed. Contemporary research by others is also touched to the extent possible in this short output. Further a point of interest is to start with classical estimation methods based on unequal probability sampling and to follow up with appropriate modelling. This has been diligently implemented as is not usually emphasised in the current literature on Small Area Estimation. Nº de ref. del artículo: 9783659136764
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Librería: preigu, Osnabrück, Alemania
Taschenbuch. Condición: Neu. Developing Small Domain Statistics: Modelling in Survey Sampling | Small area estimation | Arijit Chaudhuri | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783659136764 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Nº de ref. del artículo: 106420873
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