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An Asymmetric Area Model-Based Approach for Small Area Estimation Applied to Survey Data
Revstat Statistical Journal, 2021 The Birnbaum–Saunders distribution is asymmetrical and has received considerable attention due to its properties and its relationship with the normal distribution. In this paper, we propose a methodology for estimating the mean of small areas based on a
Marcelo Rodríguez +5 more
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Smoothing and Benchmarking for Small Area Estimation [PDF]
International Statistical Review, 2020 SummarySmall area estimation is concerned with methodology for estimating population parameters associated with a geographic area defined by a cross‐classification that may also include non‐geographic dimensions. In this paper, we develop constrained estimation methods for small area problems: those requiring smoothness with respect to similarity ...
Rebecca C. Steorts +2 more
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Weighting and imputation comparison in small area estimation
Lietuvos Matematikos Rinkinys, 2010 In this paper, different methods of nonresponse adjustment for the totals of small area domains are examined. To improve quality of estimations linear model with random parameters at domain level is used.
Vilma Nekrašaitė-Liegė
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Small area estimation in the case of nonesponse
Lietuvos Matematikos Rinkinys, 2009 In this paper the effect of model and nonresponseadjustment on different types of estimators for the totals of small area domains is examined. The empirical results are based on Monte Carlo simulations with repeated samples drawn from a finite population
Vilma Nekrašaitė-Liegė
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Precise and unbiased biomass estimation from GEDI data and the US Forest Inventory
Frontiers in Forests and Global Change, 2023 Atmospheric CO2 concentrations are dependent on land-atmosphere carbon fluxes resultant from forest dynamics and land-use changes. These fluxes are not well-constrained, in part because reliable baseline estimates of forest carbon stocks and the ...
Jamis Bruening +3 more
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An Empirical Evaluation of Small Area Estimators [PDF]
SSRN Electronic Journal, 2003 Summary: This paper compares five small area estimators. We use Monte Carlo simulation in the context of both artificial and real populations. In addition to the direct and indirect estimators, we consider the optimal composite estimator with population weights, and two composite estimators with estimated weights: one that assumes homogeneity of within
Àlex Costa, Albert Satorra, Eva Ventura
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Robust Small Area Estimation and Oversampling in the Estimation of Poverty Indicators
Survey Research Methods, 2012 There has been rising interest in research on poverty mapping over the last decade, with the European Union proposing a core of statistical indicators on poverty commonly known as Laeken Indicators. They include the incidence and the intensity of poverty
Caterina Giusti +3 more
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Small Area Estimation with Linked Data [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2020 AbstractData linkage can be used to combine values of the variable of interest from a national survey with values of auxiliary variables obtained from another source, such as a population register, for use in small area estimation. However, linkage errors can induce bias when fitting regression models; moreover, they can create non-representative ...
Salvati N. +3 more
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A Method of Complex Disclosure Risk Assessment for Microdata
Journal of Probability and StatisticsThis article proposes a method for constructing an aggregate measure of disclosure risk: the risk that a user or an intruder can derive an individual’s confidential information from a given data set.
Andrzej Młodak
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Small area estimation with covariates perturbed for disclosure limitation
Statistica, 2015 We exploit the connections between measurement error and data perturbation for disclosure limitation in the context of small area estimation. Our starting point is the model in Ybarra and Lohr (2008), where some of the covariates (all continuous) are ...
Silvia Polettini, Serena Arima
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