Explore
Causal Inference for Heterogeneous Data and Information Theory
0 Ungluers have
Faved this Work
Login to Fave
The present reprint, “Causal Inference for Heterogeneous Data and Information Theory”, is a special issue of Journal Entropy. This Special Issue belongs to the section "Information Theory, Probability, and Statistics". The reprint gathers thirteen original contributions of leading experts in the theory of causal inference, focusing namely on the utilization of instrumental variables in a causal model, estimation of average treatment effect, the role of interventions in causal models, graphical causal modeling, causal algebras, causal modeling using the theory of categories, temporal causal model, heterogeneous data, and information–theoretic approaches.
This book is included in DOAB.
Why read this book? Have your say.
You must be logged in to comment.
Rights Information
Are you the author or publisher of this work? If so, you can claim it as yours by registering as an Unglue.it rights holder.Downloads
This work has been downloaded 20 times via unglue.it ebook links.
- 20 - pdf (CC BY) at Unglue.it.
Keywords
- Approximation theory
- artificial intelligence
- BART
- Bitcoin
- causal calculus
- causal discovery
- causal fairness
- causal graph
- causal graphs
- causal inference
- causal learning
- causal machine learning
- causality
- Chain Event Graphs
- common hidden cause
- Computer science
- Computing & information technology
- conditional average treatment effects
- continuous
- correct specification
- doubly robust estimation
- dynamic systems
- econometrics software
- Economics, finance, business & management
- event cognition
- graphical models
- grouped data
- Hawkes process
- Hellinger distance
- heterogeneous treatment effects
- hidden confounder
- high-dimensional statistics
- higher-order category theory
- individualized treatment effects
- Industry & industrial studies
- Inflation
- Information technology industries
- instrumental variable
- instrumental variables
- Interventions
- Kullback–Leibler divergence
- Machine learning
- Media, information & communication industries
- misspecified models
- multilevel data
- multiple treatments
- n/a
- neural networks
- non-Gaussianity
- piecewise linear
- probabilistic models
- regularization
- responsible data science
- selection-on-observables
- semi-parametric theory
- stan
- statistical learning
- Statistics
- thema EDItEUR::U Computing and Information Technology::UY Computer science
- thresholds model
- Time
- yield spreads
Links
DOI: 10.3390/books978-3-0365-8051-7Editions