English

Max-linear models on directed acyclic graphs

Probability 2017-02-07 v2

Abstract

We consider a new recursive structural equation model where all variables can be written as max-linear function of their parental node variables and independent noise variables. The model is max-linear in terms of the noise variables, and its causal structure is represented by a directed acyclic graph. We detail the relation between the weights of the recursive structural equation model and the coefficients in its max-linear representation. In particular, we characterize all max-linear models which are generated by a recursive structural equation model, and show that its max-linear coefficient matrix is the solution of a fixed point equation. We also find a unique minimum directed acyclic graph representing the recursive structural equations of the variables. The model structure introduces a natural order between the node variables and the max-linear coefficients. This yields representations of the vector components, which are based on a minimum number of node and noise variables.

Cite

@article{arxiv.1512.07522,
  title  = {Max-linear models on directed acyclic graphs},
  author = {Nadine Gissibl and Claudia Klüppelberg},
  journal= {arXiv preprint arXiv:1512.07522},
  year   = {2017}
}

Comments

29 pages

R2 v1 2026-06-22T12:16:50.457Z