Causal Reasoning for Events in Continuous Time: A Decision - Theoretic Approach
Abstract
The dynamics of events occurring in continu-ous time can be modelled using marked point processes, or multi-state processes. Here, we review and extend the work of Røysland et al. (2015) on causal reasoning with local inde-pendence graphs for marked point processes in the context of survival analysis. We relate the results to the decision-theoretic approach of Dawid & Didelez (2010) using influence diagrams, and present additional identifying conditions. 1
Cite
Text
Didelez. "Causal Reasoning for Events in Continuous Time: A Decision - Theoretic Approach." Conference on Uncertainty in Artificial Intelligence, 2015.Markdown
[Didelez. "Causal Reasoning for Events in Continuous Time: A Decision - Theoretic Approach." Conference on Uncertainty in Artificial Intelligence, 2015.](https://mlanthology.org/uai/2015/didelez2015uai-causal/)BibTeX
@inproceedings{didelez2015uai-causal,
title = {{Causal Reasoning for Events in Continuous Time: A Decision - Theoretic Approach}},
author = {Didelez, Vanessa},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {2015},
pages = {40-45},
url = {https://mlanthology.org/uai/2015/didelez2015uai-causal/}
}