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Wyświetlanie 1-4 z 4
Tytuł:
A Comparison of Small Area and Calibration Estimators via Simulation
Autorzy:
Hidiroglou, Michael A.
Estevao, Victor M.
Powiązania:
https://bibliotekanauki.pl/articles/465930.pdf
Data publikacji:
2016
Wydawca:
Główny Urząd Statystyczny
Tematy:
area level
unit level
calibration estimates
small area estimates
simulation
Opis:
Domain estimates are typically obtained using calibration estimators that are direct or modified direct. They are direct if they strictly use data within the domain of interest. They are modified direct if they use both data within and outside the domain of interest. An alternative way of producing these estimates is through small area procedures. In this article, we compare the performance of these two approaches via a simulation. The population is generated using a hierarchical model that includes both area effects and unit level random errors. The population is made up of mutually exclusive domains of different sizes, ranging from a small number of units to a large number of units. We select many independent simple random samples of fixed size from the population and compute various estimates for each sample using the available auxiliary information. The estimates computed for the simulation included the Horvitz-Thompson estimator, the synthetic estimator (indirect estimate), calibration estimators, and unit level based estimators (small area estimate). The performance of these estimators is summarized based on their design- based properties
Źródło:
Statistics in Transition new series; 2016, 17, 1; 133-154
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Small Area Prediction under Alternative Model Specifications
Autorzy:
Erciulescu, Andreea L.
Fuller, Wayne A.
Powiązania:
https://bibliotekanauki.pl/articles/465723.pdf
Data publikacji:
2016
Wydawca:
Główny Urząd Statystyczny
Tematy:
unit level model
parametric bootstrap
double bootstrap
measurement error
auxiliary information
Opis:
Construction of small area predictors and estimation of the prediction mean squared error, given different types of auxiliary information are illustrated for a unit level model. Of interest are situations where the mean and variance of an auxiliary variable are subject to estimation error. Fixed and random specifications for the auxiliary variables are considered. The efficiency gains associated with the random specification for the auxiliary variable measured with error are demonstrated. A parametric bootstrap procedure is proposed for the mean squared error of the predictor based on a logit model. The proposed bootstrap procedure has smaller bootstrap error than a classical double bootstrap procedure with the same number of samples.
Źródło:
Statistics in Transition new series; 2016, 17, 1; 9-24
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Inferential Issues in Model-Based Small Area Estimation: Some New Developments
Autorzy:
Rao, J. N. K.
Powiązania:
https://bibliotekanauki.pl/articles/465725.pdf
Data publikacji:
2015
Wydawca:
Główny Urząd Statystyczny
Tematy:
area level models
complex parameters
informative sampling
model misspecification
robust estimation
unit level models
Opis:
Small area estimation (SAE) has seen a rapid growth over the past 10 years or so. Earlier work is covered in the author's book (Rao 2003). The main purpose of this paper is to highlight some new developments in model-based SAE since the publication of the author's book. A large part of the new theory addressed practical issues associated with the model-based approach, and we present some of those methods for area level and unit level models. We also briefly mention some new work on synthetic estimation of area means or totals based on implicit models.
Źródło:
Statistics in Transition new series; 2015, 16, 4; 491-510
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Comparison of Small Area Estimation Methods for Poverty Mapping
Autorzy:
Guadarrama, María
Molina, Isabel
Rao, J. N. K.
Powiązania:
https://bibliotekanauki.pl/articles/465671.pdf
Data publikacji:
2016
Wydawca:
Główny Urząd Statystyczny
Tematy:
area level model
non-linear parameters
empirical best estimator
hierarchical Bayes
poverty mapping
unit level models
Opis:
We review main small area estimation methods for the estimation of general nonlinear parameters focusing on FGT family of poverty indicators introduced by Foster, Greer and Thorbecke (1984). In particular, we consider direct estimation, the Fay-Herriot area level model (Fay and Herriot, 1979), the method of Elbers, Lanjouw and Lanjouw (2003) used by the World Bank, the empirical Best/Bayes (EB) method of Molina and Rao (2010) and its extension, the Census EB, and finally the hierarchical Bayes proposal of Molina, Nandram and Rao (2014). We put ourselves in the point of view of a practitioner and discuss, as objectively as possible, the benefits and drawbacks of each method, illustrating some of them through simulation studies.
Źródło:
Statistics in Transition new series; 2016, 17, 1; 41-66
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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