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Characterization of causal ancestral graphs for time series with latent confounders

Gerhardus, Andreas (2024) Characterization of causal ancestral graphs for time series with latent confounders. Annals of Statistics, 52 (1), pp. 103-130. Institute of Mathematical Statistics. doi: 10.1214/23-AOS2325. ISSN 0090-5364.

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[img] PDF - Published version
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Official URL: https://projecteuclid.org/journals/annals-of-statistics/volume-52/issue-1/Characterization-of-causal-ancestral-graphs-for-time-series-with-latent/10.1214/23-AOS2325.short


Item URL in elib:https://elib.dlr.de/203437/
Document Type:Article
Title:Characterization of causal ancestral graphs for time series with latent confounders
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Gerhardus, AndreasAndreas.Gerhardus (at) dlr.deUNSPECIFIEDUNSPECIFIED
Date:February 2024
Journal or Publication Title:Annals of Statistics
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:52
DOI:10.1214/23-AOS2325
Page Range:pp. 103-130
Publisher:Institute of Mathematical Statistics
ISSN:0090-5364
Status:Published
Keywords:Causal graph, ancestral graph, time series, latent variable, causal inference, causal discovery
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:other
DLR - Research area:Raumfahrt
DLR - Program:R - no assignment
DLR - Research theme (Project):R - no assignment, D - no assignment
Location: Jena
Institutes and Institutions:Institute of Data Science > Data Analysis and Intelligence
Deposited By: Gerhardus, Andreas
Deposited On:19 Dec 2024 10:34
Last Modified:17 Feb 2025 13:59

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