000			05292cam a2200565Mi 4500
001			ocn932063208
003			OCoLC
005			20190328114813.0
006			m o d
007			cr |||||||||||
008			150812s2015 ne o 000 0 eng d
040			_aNLE _beng _erda _epn _cNLE _dOCLCO _dOCLCQ _dOCLCF _dEBLCP _dOPELS _dU3W _dD6H _dOCLCQ _dWYU _dCUY _dZCU _dMERUC _dICG _dVT2 _dDKC
019			_a932332309
020			_a9780081005958 _q(electronic bk.)
020			_a0081005954 _q(electronic bk.)
020			_z9780081005941 _q(hbk.)
020			_a0081005946 _q(Trade Cloth)
020			_a9780081005941
024	3		_a9780081005941
035			_a(OCoLC)932063208 _z(OCoLC)932332309
050		4	_aQA276
082	0	4	_a001.422 _223
100	1		_aSingh, Sarjinder, _d1963- _eauthor.
245	1	2	_aA new concept for tuning design weights in survey sampling : jackknifing in theory and practice / _h[electronic resource] _cSarjinder Singh, Stephen Sedory, Maria Rueda, Antonio Arcos, Raghunath Arnab.
264		1	_aAmsterdam : _bAcademic Press, _c2015.
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
588	0		_aCIP data; item not viewed.
505	0		_aFront Cover; A New Concept for Tuning Design Weights in Survey Sampling: Jackknifing in Theory and Practice; Copyright; Dedication; Contents; Preface; Further studies; Acknowledgments; Chapter 1: Problem of estimation; 1.1. Introduction; 1.2. Estimation problem and notation; 1.3. Modeling of jumbo pumpkins; 1.3.1. R code; 1.4. The concept of jackknifing; 1.5. Jackknifing the sample mean; 1.6. Doubly jackknifed sample mean; 1.7. Jackknifing a sample proportion; 1.8. Jackknifing of a double suffix variable sum; 1.9. Frequently asked questions; 1.10. Exercises.
505	8		_aChapter 2: Tuning of jackknife estimator2.1. Introduction; 2.2. Notation; 2.3. Tuning with a chi-square type distance function; 2.3.1. Problem of undercoverage; 2.3.2. Estimation of variance and coverage; 2.3.3. R code; 2.3.4. Remark on tuning with a chi-square distance; 2.3.5. Numerical illustration; 2.3.6. R code used for illustration; 2.3.7. Problem of negative weights; 2.4. Tuning with dell function; 2.4.1. Estimation of variance and coverage; 2.4.2. R code; 2.4.3. Numerical illustration; 2.4.4. R code used for illustration; 2.5. An important remark; 2.6. Exercises.
505	8		_aChapter 3: Model assisted tuning of estimators3.1. Introduction; 3.2. Model assisted tuning with a chi-square distance function; 3.2.1. Estimation of variance and coverage; 3.2.2. R code; 3.3. Model assisted tuning with a dual-to-empirical log-likelihood (dell) function; 3.3.1. Estimation of variance and coverage; 3.3.2. R code; 3.4. Exercises; Chapter 4: Tuned estimators of finite population variance; 4.1. Introduction; 4.2. Tuned estimator of finite population variance; 4.3. Tuning with a chi-square distance; 4.3.1. Estimation of variance of the estimator of variance and coverage.
505	8		_a4.3.2. R code4.3.3. Remark on tuning with a chi-square distance; 4.3.4. Numerical illustration; 4.3.5. R code used for illustration; 4.3.6. F-distribution; 4.4. Tuning of estimator of finite population variance with a dual-to-empirical log-likelihood (dell) function; 4.4.1. Estimation of variance and coverage; 4.4.2. R code; 4.4.3. Numerical illustration; 4.4.4. R code used for illustration; 4.5. Alternative tuning with a chi-square distance; 4.5.1. Estimation of variance and coverage; 4.5.2. R code; 4.5.3. Numerical illustration; 4.5.4. R code used for illustration.
505	8		_a4.6. Alternative tuning with a dell function4.6.1. Estimation of variance and coverage; 4.6.2. R code; 4.6.3. Numerical illustration; 4.6.4. R code used for illustration; 4.7. Exercises; Chapter 5: Tuned estimators of correlation coefficient; 5.1. Introduction; 5.2. Correlation coefficient; 5.3. Tuned estimator of correlation coefficient; 5.3.1. Estimation of variance of the estimator of correlation coefficient and coverage; 5.3.2. R code; 5.3.3. Numerical illustration; 5.3.4. R code used for illustration; 5.4. Exercises; Chapter 6: Tuning of multicharacter survey estimators.
520			_aA New Concept for Tuning Design Weights in Survey Sampling: Jackknifing in Theory and Practice introduces the new concept of tuning design weights in survey sampling by presenting three concepts: calibration, jackknifing, and imputing where needed. This new methodology allows survey statisticians to develop statistical software for analyzing data in a more precisely and friendly way than with existing techniques.
504			_aIncludes bibliographical references and indexes.
650		0	_aSampling (Statistics)
650		7	_aSampling (Statistics) _2fast _0(OCoLC)fst01104676
650		4	_aSampling (Statistics)
650		4	_aMathematics _xProbability & Statistics _xGeneral.
655		4	_aElectronic books.
655		7	_aElectronic books. _2lcgft
700	1		_aSedory, Stephen, _eauthor.
700	1		_aRueda, Maria, _eauthor.
700	1		_aArcos, Antonio, _eauthor.
700	1		_aArnab, Raghunath, _eauthor.
776	0	8	_iPrint version: _z9780081005941
856	4	0	_3ScienceDirect _uhttp://www.sciencedirect.com/science/book/9780081005941
999			_c247254 _d247254