activity
20112021
most citedProper local scoring rules

74 citations · 319 across the 18 of their papers we have counts for

collaborators

24 papers

stat.CO2021

On some algorithms for estimation in Gaussian graphical models

Søren Højsgaard, Steffen Lauritzen

In Gaussian graphical models, the likelihood equations must typically be solved iteratively. We investigate two algorithms: A version of iterative proportional scaling which avoids…

stat.ME2020★ 1 cited

Locally associated graphical models and mixed convex exponential families

Steffen Lauritzen, Piotr Zwiernik

The notion of multivariate total positivity has proved to be useful in finance and psychology but may be too restrictive in other applications. In this paper we propose a concept o…

math.ST2020★ 26 cited

Conditional Independence in Max-linear Bayesian Networks

Carlos Améndola, Claudia Klüppelberg, Steffen Lauritzen +1

Motivated by extreme value theory, max-linear Bayesian networks have been recently introduced and studied as an alternative to linear structural equation models. However, for max-l…

math.ST2019

Harmonic Analysis of Symmetric Random Graphs

Steffen Lauritzen

This note attempts to understand graph limits as defined by Lovasz and Szegedy (2006)} in terms of harmonic analysis on semigroups. This is done by representing probability distrib…

stat.ME2019★ 23 cited

Total positivity in exponential families with application to binary variables

Steffen Lauritzen, Caroline Uhler, Piotr Zwiernik

We study exponential families of distributions that are multivariate totally positive of order 2 (MTP2), show that these are convex exponential families, and derive conditions for…

stat.ME2019

Bayesian Networks for Max-linear Models

Claudia Klüppelberg, Steffen Lauritzen

We study Bayesian networks based on max-linear structural equations as introduced in Gissibl and Klüppelberg [16] and provide a summary of their independence properties. In particu…