Notice bibliographique
- Notice
Type(s) de contenu et mode(s) de consultation : Texte noté : électronique
Auteur(s) : Rao, J. N. K. (1937-....)
Molina, Isabel (1975-....)
Titre(s) : Small area estimation [Texte électronique] / J.N.K. Rao and Isabel Molina
Édition : 2nd edition
Publication : Hoboken, New Jersey : John Wiley & Sons, Inc., 2015
Description matérielle : 1 online resource
Collection : Wiley series in survey methodology
Note(s) : Includes bibliographical references and index. - Print version record and CIP data provided by publisher.
Sujet(s) : Échantillonnage (statistique)
Estimation, Théorie de l'
Indice(s) Dewey :
519.52 (23e éd.) = Théorie de l'échantillonnage (statistique mathématique)
Identifiants, prix et caractéristiques : ISBN 9781118735855
Identifiant de la notice : ark:/12148/cb44654939k
Notice n° :
FRBNF44654939
(notice reprise d'un réservoir extérieur)
Table des matières : Direct domain estimation ; Indirect domain estimation ; Small area models ; Empirical
best linear unbiased prediction : theory ; EBLUP : basic area level model ; Basic
unit level model ; EBLUP : extensions ; Empirical Bayes (EB) method ; Hierarchical
Bayes (HB) method.
8.4 *Spatial Models ; 8.5 *Two-Fold Subarea Level Models ; 8.6 *Multivariate Nested
Error Regression Model ; 8.7 Two-Fold Nested Error Regression Model ; 8.8 *Two-Level
Model ; 8.9 *Models for Multinomial Counts ; 8.10 *EBLUP for Vectors of Area Proportions
; 8.11 *Software ; Chapter 9 Empirical Bayes (EB) Method ; 9.1 Introduction ;
9.2 Basic Area Level Model ; 9.2.1 EB Estimator ; 9.2.2 MSE Estimation ; 9.2.3
Approximation to Posterior Variance ; 9.2.4 *EB Confidence Intervals ; 9.3 Linear
Mixed Models ; 9.3.1 EB Estimation of μ i=l i Tβ+m i T v i ; 9.3.2 MSE Estimation
; 9.3.3 Approximations to the Posterior Variance ; 9.4 *EB Estimation of General
Finite Population Parameters ; 9.4.1 BP Estimator Under a Finite Population ; 9.4.2
EB Estimation Under the Basic Unit Level Model ; 9.4.3 FGT Poverty Measures ; 9.4.4
Parametric Bootstrap for MSE Estimation ; 9.4.5 ELL Estimation ; 9.4.6 Simulation
Experiments ; 9.5 Binary Data ; 9.5.1 *Case of No Co
10.3.3 Unknown σ v 2 : Gibbs Sampling ; 10.3.4 *Unknown Sampling Variances ψ i ;
10.3.5 *Spatial Model ; 10.4 *Unmatched Sampling and Linking Area Level Models ;
10.5 Basic Unit Level Model ; 10.5.1 Known σ v 2 and σ e 2 ; 10.5.2 Unknown σv 2
and σ e 2 : Numerical Integration ; 10.5.3 Unknown σ v 2 and σ e 2 : Gibbs Sampling
; 10.5.4 Pseudo-HB Estimation ; 10.6 General ANOVA Model ; 10.7 *HB Estimation
of General Finite Population Parameters ; 10.7.1 HB Estimator under a Finite Population
; 10.7.2 Reparameterized Basic Unit Level Model ; 10.7.3 HB Estimator of a General
Area Parameter ; 10.8 Two-Level Models ; 10.9 Time Series and Cross-Sectional Models
; 10.10 Multivariate Models ; 10.10.1 Area Level Model ; 10.10.2 Unit Level Model
; 10.11 Disease Mapping Models ; 10.11.1 Poisson-Gamma Model ; 10.11.2 Log-Normal
Model ; 10.11.3 Two-Level Models ; 10.12 *Two-Part Nested Error Model ; 10.13 Binary
Data ; 10.13.1 Beta-Binomial
6.1.3 Relative Efficiency of Estimators of σ v 2 ; 6.1.4 *Applications ; 6.2 MSE
Estimation ; 6.2.1 Unconditional MSE of EBLUP ; 6.2.2 MSE for Nonsampled Areas ;
6.2.3 *MSE Estimation for Small Area Means ; 6.2.4 *Bootstrap MSE Estimation ; 6.2.5
*MSE of a Weighted Estimator ; 6.2.6 Mean Cross Product Error of Two Estimators ;
6.2.7 *Conditional MSE ; 6.3 *Robust Estimation in the Presence of Outliers ; 6.4
*Practical Issues ; 6.4.1 Unknown Sampling Error Variances ; 6.4.2 Strictly Positive
Estimators of σ v 2 ; 6.4.3 Preliminary Test Estimation ; 6.4.4 Covariates Subject
to Sampling Errors ; 6.4.5 Big Data Covariates ; 6.4.6 Benchmarking Methods ; 6.4.7
Misspecified Linking Model ; 6.5 *Software ; Chapter 7 Basic Unit Level Model ;
7.1 EBLUP Estimation ; 7.1.1 BLUP Estimator ; 7.1.2 Estimation of σ v 2 and σ e
2 ; 7.1.3 *Nonnegligible Sampling Fractions ; 7.2 MSE Estimation ; 7.2.1 Unconditional
MSE of EBLUP ; 7.2.2 Unconditional MSE Estim
