Causal Inference for Heterogeneous Data and Information Theory

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https://mdpi.com/books/pdfview/book/7572Contributor(s)
Hlaváčková-Schindler, Kateřina (editor)
Language
EnglishAbstract
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.
Keywords
common hidden cause; graphical models; probabilistic models; Chain Event Graphs; interventions; causal calculus; causal fairness; responsible data science; causal discovery; Hawkes process; high-dimensional statistics; hidden confounder; causality; Bitcoin; inflation; yield spreads; approximation theory; Hellinger distance; Kullback–Leibler divergence; correct specification; misspecified models; causal inference; instrumental variables; neural networks; doubly robust estimation; semi-parametric theory; instrumental variable; causal graph; non-Gaussianity; causal graphs; dynamic systems; causal learning; time; continuous; event cognition; econometrics software; causal machine learning; statistical learning; conditional average treatment effects; individualized treatment effects; multiple treatments; selection-on-observables; piecewise linear; thresholds model; causal Inference; regularization; BART; Stan; machine learning; heterogeneous treatment effects; multilevel data; grouped data; artificial intelligence; higher-order category theory; statistics; n/aWebshop link
https://mdpi.com/books/pdfview ...ISBN
9783036580500, 9783036580517Publisher website
www.mdpi.com/booksPublication date and place
Basel, 2023Classification
Information technology industries
Computer science

