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Improved Direct Estimators for Small Areas

Chambers, R.; Chandra, H. - 2008

EBLUP, with the simple MSE estimator associated with the MBD estimator providing good coverage performance. We also report … results that indicate that the MBD estimator may be more robust than the EBLUP when the small area model is incorrectly … of variables, including variables that are unsuitable for EBLUP, e.g. variables that contain a significant proportion of …

Persistent link: https://www.econbiz.de/10009457583

Outlier Robust Small Area Estimation

Chambers, R.; Chandra, H.; Salvati, N.; Tzavidis, N. - 2009

Outliers are a well-known problem in survey estimation, and a variety of approaches have been suggested for dealing with them in this context. However, when the focus is on small area estimation using the survey data, much less is known – even though outliers within a small area sample are...

Persistent link: https://www.econbiz.de/10009457409

Small area estimation: an empirical best linear unbiased prediction approach

Li, Huilin - 2007

prediction (EBLUP) andits inferences under the general Fay-Herriot small area model.Considering that the currently used variance … provide a concrete proof for the positiveness andconsistency of both ADM estimators.We also propose EBLUP estimator of $\theta … themethod-of-moments, REML, ML and FH methods could be all zero. Weobserve that ADM methods produce EBLUP's which generally put …

Persistent link: https://www.econbiz.de/10009450971

Adjusting economic estimates in business surveys

Ugarte, M. D.; Militino, A. F.; Goicoa, T. - In: Journal of Applied Statistics 35 (2008) 11, pp. 1253-1265

Statistics for small areas within larger regions are recently required for many economic variables. However, when adding the estimates of the small areas within the larger regions, the results do not match up to those obtained with the appropriate estimator originally derived for the larger...

Persistent link: https://www.econbiz.de/10005458376

RELAIS: La stazionarietà locale nella stima della povertà relativa per piccole aree

Benedetti, Roberto; Rinaldelli, Claudia - In: Rivista di statistica ufficiale 9 (2007) 2-3, pp. 69-87

This paper proposes a local stationarity approach in EBLUP estimation with the aim to improve the reliability of …

Persistent link: https://www.econbiz.de/10010821631

Small Area Estimation Methods for Socio-Economic Indicators in Household Surveys

D'ALO', Michele; CONSIGLIO, Loredana DI; FALORSI, Stefano; … - In: Rivista Internazionale di Scienze Sociali 116 (2008) 4, pp. 419-442

Small area estimation techniques are becoming more and more important for the production of official data. Since 2002 ISTAT has applied small area estimation methods to disseminate estimates of employment and unemployment rates for local labour market areas; furthermore several experimental...

Persistent link: https://www.econbiz.de/10010878175

Mixed model prediction and small area estimation

Jiang, Jiming; Lahiri, P. - In: TEST: An Official Journal of the Spanish Society of … 15 (2006) 1, pp. 1-96

Persistent link: https://www.econbiz.de/10005759551

Temporal-like bivariate fay-herriot model : leveraging past responses and advanced preprocessing for enhanced small area estimation of growing stock volume

Georgakis, Aristeidis; Papageorgiou, Vasileios E.; … - In: Operations research forum 5 (2024) 1, pp. 1-28

Persistent link: https://www.econbiz.de/10014517534

Smoothing sparse and unevenly sampled curves using semiparametric mixed models: an application to online auctions

Reithinger, Florian; Jank, Wolfgang; Tutz, Gerhard; … - 2006

Functional data analysis can be challenging when the functional objects are sampled only very sparsely and unevenly. Most approaches rely on smoothing to recover the underlying functional object from the data which can be difficult if the data is irregularly distributed. In this paper we present...

Persistent link: https://www.econbiz.de/10010266159

Flexible semiparametric mixed models

Tutz, Gerhard; Reithinger, Florian - 2005

In linear mixed models the influence of covariates is restricted to a strictly parametric form. With the rise of semi- and nonparametric regression also the mixed model has been expanded to allow for additive predictors. The common approach uses the representation of additive models as mixed...

Persistent link: https://www.econbiz.de/10010266248