consequenceCovid {bnRep} | R Documentation |
consequenceCovid Bayesian Network
Description
Global sensitivity analysis of uncertain parameters in Bayesian networks.
Format
A discrete Bayesian network including demographic information of the respondents of the Eurobarometer 93.1 together with their opinion about how the COVID-19 emergency was handled by local authorities and its consequences in the long term. The Bayesian network was learned as in the referenced paper. The vertices are:
- AGE
How old are you? (18-30, 30-50, 51-70, 70+);
- LIFESAT
On the whole, are you satisfied with the life you lead? (Yes, No);
- TRUST
Do you trust or not the people in your country? (Yes, No);
- SATMEAS
In general, are you satisfied with the measures taken to fight the Coronavirus outbreak by your government? (Yes, No);
- HEALTH
Thinking about the measures taken by the public authorities in your country to fight the Coronavirus and its effects, would you say that they... (Focus too much on health, Focus too much on economivcs, Are balanced);
- JUSTIFIED
Thinking about the measures taken by the public authorities in your country to fight the Coronavirus and its effects, would you say that they were justfied? (Yes, No);
- PERSONALFIN
The Coronavirus outbreak will have serious economic consequences for you personally (Agree, Disagree, Don't know);
- COUNTRYFIN
The Coronavirus outbreak will have serious economic consequences for your country (Agree, Disagree, Don't know);
- INFO
Which of the following was your primary source of information during the Coronavirus outbreak? (Television, Written press, Radio, Websites, Social networks);
- COPING
Thinking about the measures taken to fight the Coronavirus outbreak, in particular the confinement measures, would you say that it was an experience...? (Easy to cope with, Both easy and difficult to cope with, Difficult to cope with);
- POLITICS
In political matters people talk of 'the left' and 'the right'. How would you place your views on this scale? (Left, Centre, Right, Don't know);
- OCCUPATION
Are you currently working? (Yes, No);
- GENDER
What is your sex? (Male, Female);
- COMMUNITY
Would you say you live in a... (Rural area or village, Small or middle sized town, Large town);
- CLASS
Do you see yourself and your household belonging to...? (Working class, Lower class, Middle class, Upper class);
Value
An object of class bn.fit
. Refer to the documentation of bnlearn
for details.
References
Ballester-Ripoll, R., & Leonelli, M. (2024). Global Sensitivity Analysis of Uncertain Parameters in Bayesian Networks. arXiv preprint arXiv:2406.05764.