M-quantile models for small area estimation
نویسندگان
چکیده
منابع مشابه
M-quantile Models for Small Area Estimation
Small area estimation techniques are employed when sample data are insufficient for acceptably precise direct estimation in domains of interest. These techniques typically rely on regression models that use both covariates and random effects to explain variation between domains. However, such models also depend on strong distributional assumptions, require a formal specification of the random p...
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The effective use of spatial information, that is the geographic locations of population units, in a regression model-based approach to small area estimation is an important practical issue. One approach for incorporating such spatial information in a small area regression model is via Geographically Weighted Regression (GWR). In GWR the relationship between the outcome variable and the covaria...
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The demand of reliable statistics for small areas, when only reduced sizes of the samples are available, has promoted the development of small area estimation methods. In particular, an approach that is now widely used is based on linear mixed models. Chambers & Tzavidis (2006) have recently proposed an approach for small area estimation that is based on M-quantile models. However, when the fun...
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Extended Abstract. In recent years, needs for small area estimations have been greatly increased for large surveys particularly household surveys in Sta­ tistical Centre of Iran (SCI), because of the costs and respondent burden. The lack of suitable auxiliary variables between two decennial housing and popula­ tion census is a challenge for SCI in using these methods. In general, the...
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Small area estimation is conventionally concerned with the estimation of small area averages and totals. More recently emphasis has been also placed on the estimation of poverty indicators and of key quantiles of the small area distribution function using robust models for example, the M-quantile small area model (Chambers and Tzavidis, 2006). In parallel to point estimation, Mean Squared Error...
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ژورنال
عنوان ژورنال: Biometrika
سال: 2006
ISSN: 1464-3510,0006-3444
DOI: 10.1093/biomet/93.2.255