Estimating long-term causal effects from short-term experiments and long-term observational data with unobserved confounding.
Graham Van GoffrierLucas MaystreCiarán Mark Gilligan-LeePublished in: CLeaR (2023)
Keyphrases
- long term
- short term
- causal effects
- observational data
- structural equation models
- causal relations
- experimental data
- causal relationships
- linear models
- directed acyclic graph
- causal discovery
- short term and long term
- long term memory
- medium term
- causal structure
- causal models
- latent variables
- causal bayesian networks
- sample size
- short and long term
- bayesian networks
- forecasting model
- load forecasting
- prior knowledge
- observed variables
- optimal solution
- arima model
- decision making