Estimating long-term causal effects from short-term experiments and long-term observational data with unobserved confounding.
Graham Van GoffrierLucas MaystreCiarán M. Gilligan-LeePublished in: CoRR (2023)
Keyphrases
- long term
- short term
- causal effects
- observational data
- structural equation models
- causal relations
- experimental data
- short term and long term
- linear models
- directed acyclic graph
- causal relationships
- causal structure
- long term memory
- causal discovery
- causal models
- causal bayesian networks
- latent variables
- load forecasting
- medium term
- sample size
- forecasting model
- neural network
- short and long term
- temporal information
- arima model
- feature space
- support vector
- data mining