Effective Transformation-Based Variable Selection Under Two-Fold Subarea Models in Small Area Estimation

Cai, Song; Rao, J. N. K.; Dumitrescu, Laura; Chatrchi, Golshid

doi:10.21307/stattrans-2020-031

Autor

Cai Song (Carleton University, Ottawa, ON, Canada), Rao J. N. K. (Carleton University, Ottawa, ON, Canada), Dumitrescu Laura (Victoria University of Wellington, Wellington, New Zealand), Chatrchi Golshid (Statistics Canada, Ottawa, Ontario, Canada)

Tytuł

Effective Transformation-Based Variable Selection Under Two-Fold Subarea Models in Small Area Estimation

Źródło

Statistics in Transition, 2020, vol. 21, nr 4 Special Issue, s. 68-83, tab., dodatki, bibliogr. s. 78-79

Słowa kluczowe

Statystyka małych obszarów, Dobór zmiennych, Modele statystyczne
Small area estimates, Variables selection, Statistical models

Uwagi

summ.

Abstrakt

We present a simple yet effective variable selection method for the two-fold nested subarea model, which generalizes the widely-used Fay-Herriot area model. The twofold subarea model consists of a sampling model and a linking model, which has a nested-error model structure but with unobserved responses. To select variables under the two-fold subarea model, we first transform the linking model into a model with the structure of a regular regression model and unobserved responses. We then estimate an information criterion based on the transformed linking model and use the estimated information criterion for variable selection. The proposed method is motivated by the variable selection method of Lahiri and Suntornchost (2015) for the Fay-Herriot model and the variable selection method of Li and Lahiri (2019) for the unit-level nested-error regression model. Simulation results show that the proposed variable selection method performs significantly better than some naive competitors, especially when the variance of the area-level random effect in the linking model is large. (original abstract)

Dostępne w

Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka SGH im. Profesora Andrzeja Grodka
Biblioteka Główna Uniwersytetu Ekonomicznego w Katowicach

Pełny tekst

Bibliografia

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Cytowane przez

ISSN

1234-7655

Język

eng

URI / DOI

BazEkon - Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie

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