Skip to content

Advertisement

EPJ Data Science
EPJ Data Science Cover Image
  • Erratum
  • Open Access

Erratum to: Improving official statistics in emerging markets using machine learning and mobile phone data

  • 1Email author,
  • 2,
  • 2,
  • 3, 4,
  • 1, 5 and
  • 5, 6, 7
EPJ Data Science20176:8

https://doi.org/10.1140/epjds/s13688-017-0106-8

©  The Author(s) 2017

  • Received: 1 June 2017
  • Accepted: 1 June 2017
  • Published:

The original article was published in EPJ Data Science 2017 6:3

1 Erratum

Upon publication of the original article [1], it was noticed that in the Availability of data materials section, the link to the code ‘https://github.com/eamanj/demographics_prediction’ was incorrectly given as ‘https://github.edu/eamanj/demographics_prediction’. This has now been acknowledged and corrected in this erratum.

Notes

Declarations

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors’ Affiliations

(1)
Institute for Data, Systems and Society, Massachusetts Institute of Technology, 50 Ames Street, E18-407A, Cambridge, MA 02142, USA
(2)
Telenor Research, Snarøyveien 30, Oslo, 1331, Norway
(3)
Flowminder, Roslagsgatan, Stockholm, Sweden
(4)
Department of Public Health Sciences, Karolinska Institute, SE-171 77, Stockholm, Sweden
(5)
Media Lab, Massachusetts Institute of Technology, 20 Ames Street, E14, Cambridge, MA 02142, USA
(6)
Department of Computing, Imperial College London, 180 Queens Gate, London, SW7 2RH, UK
(7)
Data Science Institute, William Penney Laboratory, Imperial College London, London, SW7 2RH, UK

References

  1. Jahani E, Sundsøy P, Bjelland J, Bengtsson L, de Montjoye YA (2017) Improving official statistics in emerging markets using machine learning and mobile phone data. EPJ Data Sci 6:1. doi:10.1140/epjds/s13688-017-0099-3 View ArticleGoogle Scholar

Copyright

© The Author(s) 2017

Advertisement