IDEAS home Printed from https://ideas.repec.org/a/spr/testjl/v30y2021i2d10.1007_s11749-021-00767-x.html
   My bibliography  Save this article

Correction to: Small area estimation of proportions under area-level compositional mixed models

Author

Listed:
  • María Dolores Esteban

    (Universidad Miguel Hernández de Elche)

  • María José Lombardía

    (Universidade da Coruña)

  • Esther López-Vizcaíno

    (Instituto Galego de Estatística)

  • Domingo Morales

    (Universidad Miguel Hernández de Elche)

  • Agustín Pérez

    (Universidad Miguel Hernández de Elche)

Abstract

The article Small area estimation of proportions under area-level compositional mixed models, written by María Dolores Esteban, María José Lombardía, Esther López-Vizcaíno, Domingo Morales & Agustín Pérez, was originally published Online First without Open Access. After publication in volume 29, issue 3, page 793–818, the author decided to opt for Open Choice and to make the article an Open Access publication. Therefore, the copyright of the article has been changed to © Authors 2021and the article is forthwith distributed under the terms of the Creative Commons Attribution.

Suggested Citation

  • María Dolores Esteban & María José Lombardía & Esther López-Vizcaíno & Domingo Morales & Agustín Pérez, 2021. "Correction to: Small area estimation of proportions under area-level compositional mixed models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 527-528, June.
  • Handle: RePEc:spr:testjl:v:30:y:2021:i:2:d:10.1007_s11749-021-00767-x
    DOI: 10.1007/s11749-021-00767-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11749-021-00767-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11749-021-00767-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yue Wang & Dengjiao Liao & Bin Yan & Xinhai Lu, 2023. "Employment of Land-Expropriated Farmers: The Effects of Land Expropriation and Gender Difference," Land, MDPI, vol. 12(10), pages 1-19, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:testjl:v:30:y:2021:i:2:d:10.1007_s11749-021-00767-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.