Loading...
Loading...

Go to the content (press return)

Preprocessing alternatives for compositional data related to water, sanitation and hygiene

Author
Quispe-Coica, F.A.; Pérez-Foguet, A.
Type of activity
Journal article
Journal
Science of the total environment
Date of publication
2020-06
Volume
743
First page
140519:1
Last page
140519:15
DOI
10.1016/j.scitotenv.2020.140519
Project funding
Engineering Sciences and Global Development
TRANSfer and METhodological development of COmpositional DAta-analytic techniques for applied sciences and engineering
Repository
http://hdl.handle.net/2117/331778 Open in new window
URL
https://www.sciencedirect.com/science/article/pii/S0048969720340419 Open in new window
Abstract
The Sustainable Development Goals (SDGs) 6.1 and 6.2 measure the progress of urban and rural populations in their access to different levels of water, sanitation and hygiene (WASH) services, based on multiple sources of information. Service levels add up to 100%; therefore, they are compositional data (CoDa). Despite evidence of zero value, missing data and outliers in the sources of information, the treatment of these irregularities with different statistical techniques has not yet been analyze...
Citation
Quispe-Coica, F.A.; Pérez-Foguet, A. Preprocessing alternatives for compositional data related to water, sanitation and hygiene. "Science of the total environment", Juny 2020, vol. 743, p. 140519:1-140519:15.
Keywords
Global monitoring, Mahalanobis distance, Outliers, Robust regression
Group of research
EScGD - Engineering Sciences and Global Development

Participants