Difference-Type Estimators for Estimation of Mean in The Presence of Measurement Error PDF Download

Author: Hemant K. Verma
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 21

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Book Description
In this paper we have suggested difference-type estimator for estimation of population mean of the study variable y in the presence of measurement error using auxiliary information.

Author: Jack Allen
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 15

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Book Description
This paper proposes a family of estimators of population mean using information on several auxiliary variables and analyzes its properties in the presence of measurement errors.

Author: Rajesh Singh
Publisher: Infinite Study
ISBN: 1599732750
Category : Population
Languages : en
Pages : 73

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Book Description
The purpose of writing this book is to suggest some improved estimators using auxiliary information in sampling schemes like simple random sampling, systematic sampling and stratified random sampling. This volume is a collection of five papers, written by nine co-authors (listed in the order of the papers): Rajesh Singh, Mukesh Kumar, Manoj Kr. Chaudhary, Cem Kadilar, Prayas Sharma, Florentin Smarandache, Anil Prajapati, Hemant Verma, and Viplav Kr. Singh. In first paper dual to ratio-cum-product estimator is suggested and its properties are studied. In second paper an exponential ratio-product type estimator in stratified random sampling is proposed and its properties are studied under second order approximation. In third paper some estimators are proposed in two-phase sampling and their properties are studied in the presence of non-response. In fourth chapter a family of median based estimator is proposed in simple random sampling. In fifth paper some difference type estimators are suggested in simple random sampling and stratified random sampling and their properties are studied in presence of measurement error.

Author: Rajesh Singh
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 11

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Book Description
This paper considers the problem of estimating the population mean using information on auxiliary variable in presence of non response. Exponential ratio and exponential product type estimators have been suggested and their properties are studied. An empirical study is carried out to support the theoretical results.

Author: Hsing-Me Chen
Publisher:
ISBN:
Category : Error analysis (Mathematics)
Languages : en
Pages : 282

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Book Description

Author: Rajesh Singh
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 9

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Book Description
In this chapter, we have suggested an improved estimator for estimating the population mean in stratified sampling in presence of auxiliary information. The mean square error (MSE) of the proposed estimator have been derived under large sample approximation.

Author: Manoj K. Chaudhary
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 11

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Book Description
The objective of the present paper is to propose a family of separate-type estimators of population mean in stratified random sampling in presence of non response based on the family of estimators proposed by Khoshnevisan et al. (2007)

Author: Wayne A. Fuller
Publisher: John Wiley & Sons
ISBN: 0470317337
Category : Mathematics
Languages : en
Pages : 474

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Book Description
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "The effort of Professor Fuller is commendable . . . [the book] provides a complete treatment of an important and frequently ignored topic. Those who work with measurement error models will find it valuable. It is the fundamental book on the subject, and statisticians will benefit from adding this book to their collection or to university or departmental libraries." -Biometrics "Given the large and diverse literature on measurement error/errors-in-variables problems, Fuller's book is most welcome. Anyone with an interest in the subject should certainly have this book." -Journal of the American Statistical Association "The author is to be commended for providing a complete presentation of a very important topic. Statisticians working with measurement error problems will benefit from adding this book to their collection." -Technometrics " . . . this book is a remarkable achievement and the product of impressive top-grade scholarly work." -Journal of Applied Econometrics Measurement Error Models offers coverage of estimation for situations where the model variables are observed subject to measurement error. Regression models are included with errors in the variables, latent variable models, and factor models. Results from several areas of application are discussed, including recent results for nonlinear models and for models with unequal variances. The estimation of true values for the fixed model, prediction of true values under the random model, model checks, and the analysis of residuals are addressed, and in addition, procedures are illustrated with data drawn from nearly twenty real data sets.

Author: John P. Buonaccorsi
Publisher: CRC Press
ISBN: 1420066587
Category : Mathematics
Languages : en
Pages : 465

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Book Description
Over the last 20 years, comprehensive strategies for treating measurement error in complex models and accounting for the use of extra data to estimate measurement error parameters have emerged. Focusing on both established and novel approaches, Measurement Error: Models, Methods, and Applications provides an overview of the main techniques and illu

Author: Olufadi Yunusa
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 13

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Book Description
In this paper, we propose a new estimator for estimating the finite population mean using two auxiliary variables. The expressions for the bias and mean square error of the suggested estimator have been obtained to the first degree of approximation and some estimators are shown to be a particular member of this estimator.