Robust small area estimation

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August undefined, 2024

WebSep 1, 2009 · Request PDF Robust Small Area Estimation Small area estimation has received considerable attention in recent years because of growing demand for small … WebRobust Unit-Level Small Area Estimation: A Fast Algorithm for Large Datasets. Austrian Journal of Statistics 41 (4), pp. 243–265. URL: …

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http://www.asasrms.org/Proceedings/y2009/Files/302861.pdf WebRobust small area estimation is studied under a simple random effects model consisting of a basic (or fixed effects) model and a linking model that treats the fixed effects as realizations of a random variable. Under this model a model-assisted estimator of a small area mean is obtained. This estimator depends on the survey weights and remains ... meeting notes in teams meeting

Robust Bayesian small area estimation based on quantile regression …

WebNov 2, 2024 · Functions for Robust Bayesian Small Area Estimation. WebAlso, the estimates of the model parameters underpinning the estimator will themselves be affected by the sample outliers. In order to address these challenges, Chambers et al. (2014) considered the ways in which robust survey estimation procedures could be adapted to small area estimation. name of north carolina

Robust estimation for small domains in business surveys - arXiv

Small Area Estimation - Census.gov

WebMay 1, 2024 · Quantile regression has been introduced in small area estimation as a distribution-free robust alternative to linear mixed models, thereby we focus on the ability of quantile regression based predictors to deal with outliers. We consider the same simulation exercise presented in Chambers et al. (2014), Section 5, simply adding new. WebFeb 2, 2014 · This presents a semiparametric approach to small area prediction that reduces the need for parametric assumptions and allows for outlier robust estimation. The results … name of noble gasesWebwhere. formula defines the fixed-effect part of the model (the ~ operator separates dependent and independent variables; by default, the model includes a regression intercept),; area specifies the area-level random effect (variable CountyName serves as area identifier; note that the argument area is also a formula object),; data specifies the data.frame (here, … meeting notes in ms teams

"WebSep 16, 2024 · The small area estimation literature has shown that multivariate small area estimators, where correlations among response variables are taken into account, provide more efficient estimates than the traditional univariate approaches. However, the estimation problem of multivariate proportions has not been studied yet. " - Robust small area estimation

Robust small area estimation

http://www.stat.ualberta.ca/people/prasad/papers/surveymeth.pdf WebMar 8, 2024 · Small area estimation (SAE) encompasses a wide range of methods (Rao & Molina, 2015) that have become a major component in the official statistician's toolkit, with many applications to a wide range of variables and domains in many different types of surveys. (We will use the terms domain and area interchangeably.)

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WebSmall area estimation has received considerable attention in recent years because of growing demand for small area statistics. Basic area‐level and unit‐level models have been studied in the literatu... WebJul 27, 2009 · Dans cet article, les auteurs étudient les propriétés de robustesse des estimateurs classiques et ils proposent une méthode robuste pour l'estimation de petits …

WebApr 11, 2024 · The ICESat-2 mission The retrieval of high resolution ground profiles is of great importance for the analysis of geomorphological processes such as flow processes (Mueting, Bookhagen, and Strecker, 2024) and serves as the basis for research on river flow gradient analysis (Scherer et al., 2024) or aboveground biomass estimation (Atmani, … WebJun 23, 2024 · However, small area estimation methods are model-based so that the validity of the estimates depends on the model assumptions. In this study, we explore a type of …

http://www.stat.ualberta.ca/people/prasad/papers/surveymeth.pdf WebRobust Small Area Estimation under Spatial Non-stationarity. Claudia Baldermann, Claudia Baldermann. Institute of Statistics and Econometrics, Freie Universität Berlin, Berlin, Germany ... The effective use of spatial information in a regression-based approach to small area estimation is an important practical issue. One approach to account ...

WebOct 25, 2024 · Robust Small Area Estimation: a Vignette Tobias Schoch December 29, 2011: rsae 0.1-4 Contents 1 Introduction2 2 Getting started2 3 Setting up a model3 ... (Robust) Estimation Having set up our model, we consider estimating the parameters of the Gaussian core model by di erent methods. All tting is done using the following workhorse function

WebRobust parameter estimation We define the robust estimator of as , where is given in ( 6 ). Then the robust estimator satisfies (10) We use a Newton–Raphson algorithm to solve these estimating equations; the derivatives are given in the proof of Theorem 2 in the Supplementary Material. meeting notes how toWebsmall area estimation methods that are more robust in a certain way In practice, a particular statistical method is chosen for various reasons, which may be scientific, economic, or political; once a method is adopted, it is often not easy to make substantial changes … meeting notes in teams recurring meetingsWebOct 25, 2024 · robust (i.e. bounded-in uence estimating equation) methods for model A: • Huber-type M-estimation, using a slight generalization of Huber’s Proposal 2 to estimate … meeting notes in teams channelWebDans cet article, les auteurs étudient les propriétés de robustesse des estimateurs classiques et ils proposent une méthode robuste pour l'estimation de petits domaines qui … name of nuclear bombs dropped on japanWebOct 30, 2024 · The small area estimation with discrete binary or count responses requires intensive computation for both classical ML and proposed robust methods, since we … meeting notes in teams not showingWebAug 26, 2024 · Empirical Bayes small area estimation based on the well-known Fay-Herriot model may produce unreliable estimates when outlying areas exist. Existing robust methods against outliers or model misspecification are generally inefficient when the assumed distribution is plausible. This paper proposes a simple modification of the standard … meeting notes in teams missingWebTitle Robust Small Area Estimation Version 0.2 Description Empirical best linear unbiased prediction (EBLUP) and robust prediction of the area-level means under the basic unit … meeting notes missing in teams