Framework for inferring empirical causal graphs from binary data to support multidimensional poverty analysis-Reference-Cited by-同舟云学术

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Framework for inferring empirical causal graphs from binary data to support multidimensional poverty analysis

Published:2023-05 Issue:5 Volume:9 Page:e15947
ISSN:2405-8440
Container-title:Heliyon
language:en
Short-container-title:Heliyon

Author:

Amornbunchornvej Chainarong^ORCID,Surasvadi Navaporn^ORCID,Plangprasopchok Anon,Thajchayapong Suttipong

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference56 articles.

1. The contribution of data-driven technologies in achieving the sustainable development goals;Bachmann;Sustainability,2022

2. Multidimensional poverty index 2010: research briefing;Alkire,2010

3. The global multidimensional poverty index (mpi) 2021;Alkire,2021

4. Acute multidimensional poverty: a new index for developing countries;Alkire,2010

5. Identifying linear models in multi-resolution population data using minimum description length principle to predict household income;Amornbunchornvej;ACM Trans. Knowl. Discov. Data,2021

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Income, education, and other poverty-related variables: A journey through Bayesian hierarchical models;Heliyon;2024-03

2. BiCausality: Binary Causality Inference Framework;CRAN: Contributed Packages;2022-05-26

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