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Title:

Recursive max-linear models with propagating noise

Document type:
Zeitungsartikel
Author(s):
Buck, J.; Klüppelberg, C.
Abstract:
Recursive max-linear vectors model causal dependence between node variables by a structural equation model, expressing each node variable as a max-linear function of its parental nodes in a directed acyclic graph (DAG) and some exogenous innovation. For such a model, there exists a unique minimum DAG, represented by the Kleene star matrix of its edge weight matrix, which identifies the model and can be estimated. For a more realistic statistical modeling we introduce some random observational no...     »
Keywords:
graphical model, Bayesian network, directed acyclic graph, extreme value analysis, max-linear model, noisy model, regular variation
Dewey Decimal Classification:
510 Mathematik
Journal title:
Electronic Journal of Statistics
Year:
2021
Journal volume:
15
Year / month:
2021-10
Quarter:
4. Quartal
Month:
Oct
Journal issue:
2
Pages contribution:
4770-4822
Language:
en
Fulltext / DOI:
doi:doi:10.1214/21-EJS1903
Publisher:
Institute of Mathematical Statistics and the Bernoulli Society
E-ISSN:
1935-7524
Status:
Verlagsversion / published
Submitted:
29.02.2020
Accepted:
01.10.2021
TUM Institution:
Lehrstuhl für Mathematische Statistik
Format:
Text
 BibTeX