Erratum
Open Access
Erratum to: Improving official statistics in emerging markets using machine learning and mobile phone data
Received: 1 June 2017
Accepted: 1 June 2017
Published: 8 June 2017
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
(2)
Telenor Research
(3)
Flowminder
(4)
Department of Public Health Sciences, Karolinska Institute
(5)
Media Lab, Massachusetts Institute of Technology
(6)
Department of Computing, Imperial College London
(7)
Data Science Institute, William Penney Laboratory, Imperial College London
References
- 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:https://doi.org/10.1140/epjds/s13688-017-0099-3 View ArticleGoogle Scholar
Copyright
© The Author(s) 2017
