Small Area Estimation of Proportion-Based Indicators

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F23%3A00363311" target="_blank" >RIV/68407700:21340/23:00363311 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1007/978-3-031-04137-2_27" target="_blank" >https://doi.org/10.1007/978-3-031-04137-2_27</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-04137-2_27" target="_blank" >10.1007/978-3-031-04137-2_27</a>

Result language

angličtina

Original language name

Small Area Estimation of Proportion-Based Indicators

Original language description

This paper considers a unit-level multinomial model with logit link for small area estimation of proportion-based socioeconomic indicators. For a labour force survey, some of these indicators are totals of unemployed people, proportions of inactive people, unemployment rates or entropy indexes. A Broyden quasi-Newton algorithm is proposed to calculate the method-of-moment and maximum likelihood estimators of the model parameters. Model-based predictors of small area indicators are derived and their mean squared errors are estimated by parametric bootstrap.

Czech name

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Czech description

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Type

C - Chapter in a specialist book

CEP classification

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OECD FORD branch

10103 - Statistics and probability

Project

<a href="/en/project/EF16_019%2F0000778" target="_blank" >EF16_019/0000778: Center for advanced applied science</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Book/collection name

Trends in Mathematical, Information and Data Sciences

ISBN

978-3-031-04136-5

Number of pages of the result

9

Pages from-to

329-337

Number of pages of the book

456

Publisher name

Springer

Place of publication

Cham

UT code for WoS chapter

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