65 citations · 123 across the 3 of their papers we have counts for
8 papers
Interpreting the Ising Model: The Input Matters
Jonas Haslbeck, Sacha Epskamp, Maarten Marsman +1
The Ising model is a model for pairwise interactions between binary variables that has become popular in the psychological sciences. It has been first introduced as a theoretical m…
Moderated Network Models
Jonas Haslbeck, Denny Borsboom, Lourens Waldorp
Pairwise network models such as the Gaussian Graphical Model (GGM) are a powerful and intuitive way to analyze dependencies in multivariate data. A key assumption of the GGM is tha…
A Tutorial on Estimating Time-Varying Vector Autoregressive Models
Jonas M B Haslbeck, Laura F Bringmann, Lourens J Waldorp
Time series of individual subjects have become a common data type in psychological research. These data allow one to estimate models of within-subject dynamics, and thereby avoid t…
How Predictable are Symptoms in Psychopathological Networks? A Reanalysis of 18 Published Datasets
Jonas M B Haslbeck, Eiko I Fried
Background Network analyses on psychopathological data focus on the network structure and its derivatives such as node centrality. One conclusion one can draw from centrality measu…
How well do Network Models predict Observations? On the Importance of Predictability in Network Models
Jonas Haslbeck, Lourens J Waldorp
Network models are an increasingly popular way to abstract complex psychological phenomena. While the study of the structure of network models has led to many important insights, l…
Estimating the Number of Clusters via Normalized Cluster Instability
Jonas M. B. Haslbeck, Dirk U. Wulff
We improve current instability-based methods for the selection of the number of clusters in cluster analysis by developing a normalized cluster instability measure that correct…
Structure estimation for mixed graphical models in high-dimensional data
Jonas M. B. Haslbeck, Lourens J. Waldorp
Undirected graphical models are a key component in the analysis of complex observational data in a large variety of disciplines. In many of these applications one is interested in…
mgm: Estimating Time-Varying Mixed Graphical Models in High-Dimensional Data
Jonas M. B. Haslbeck, Lourens J. Waldorp
We present the R-package mgm for the estimation of k-order Mixed Graphical Models (MGMs) and mixed Vector Autoregressive (mVAR) models in high-dimensional data. These are a useful…