Causal Inference for Heterogeneous Data and Information Theory

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 the...

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Format:	Online
Idioma:	anglès
Publicat:	MDPI - Multidisciplinary Digital Publishing Institute 2023
Matèries:	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/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science
Accés en línia:	ONIX_20230808_9783036580500_27
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Causal Inference for Heterogeneous Data and Information Theory

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