A unified Monte-Carlo jackknife for small area estimation after model selection

DOI10.4310/AMSA.2018.V3.N2.A2zbMath1403.62020arXiv1602.05238OpenAlexW2964133458WikidataQ129382822 ScholiaQ129382822MaRDI QIDQ1797854

Jiming Jiang, Thuan Nguyen, Parthasarathi Lahiri

Publication date: 22 October 2018

Published in: Annals of Mathematical Sciences and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1602.05238

zbMATH Keywords

Monte Carlomodel selectionjackknifesmall area estimationmeasure of uncertaintycomputer intensivelog-MSPEsecond-order unbiasedness

Mathematics Subject Classification ID

Sampling theory, sample surveys (62D05) Bootstrap, jackknife and other resampling methods (62F40)

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Small area estimation with mixed models: a review ⋮ Selection model for domains across time: application to labour force survey by economic activities ⋮ An empirical comparison of various MSPE estimators and associated prediction intervals for small area means ⋮ Empirical best prediction under a nested error model with log transformation ⋮ Observed best selective prediction in small area estimation ⋮ Classified mixed logistic model prediction ⋮ A new classified mixed model predictor ⋮ A class of general adjusted maximum likelihood methods for desirable mean squared error estimation of EBLUP under the Fay-Herriot small area model

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