Causal discovery in heavy-tailed models
From MaRDI portal
Publication:820829
DOI10.1214/20-AOS2021zbMath1475.62130arXiv1908.05097OpenAlexW3187292592MaRDI QIDQ820829
Nicola Gnecco, Nicolai Meinshausen, Jonas Peters, Sebastian Engelke
Publication date: 28 September 2021
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1908.05097
Nonparametric regression and quantile regression (62G08) Nonparametric estimation (62G05) Statistics of extreme values; tail inference (62G32)
Related Items
Total positivity in multivariate extremes, Modeling panels of extremes, Causality in extremes of time series, Causal modelling of heavy-tailed variables and confounders with application to river flow
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Cites Work
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- Extremes on river networks
- CAM: causal additive models, high-dimensional order search and penalized regression
- Estimation of causal effects using linear non-Gaussian causal models with hidden variables
- Regularly varying multivariate time series
- Causation, prediction, and search
- A simple general approach to inference about the tail of a distribution
- Independent component analysis, a new concept?
- Max-linear models on directed acyclic graphs
- Multiple block sizes and overlapping blocks for multivariate time series extremes
- PC algorithm for Gaussian copula graphical models
- Independence properties of directed markov fields
- Identifiability and estimation of recursive max‐linear models
- Graphical Models for Extremes
- Causal Inference for Statistics, Social, and Biomedical Sciences
- Investigating Causal Relations by Econometric Models and Cross-spectral Methods
- Estimation of the Marginal Expected Shortfall: the Mean When a Related Variable is Extreme
- ParceLiNGAM: A Causal Ordering Method Robust Against Latent Confounders
- Structural Intervention Distance for Evaluating Causal Graphs
- Identifiability of Gaussian structural equation models with equal error variances
- Three approaches to the quantitative definition of information*
- An introduction to statistical modeling of extreme values
