Blog Archives

Predictability in Network Models

October 31, 2016
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Predictability in Network Models

Network models have become a popular way to abstract complex systems and gain insights into relational patterns among observed variables in almost any area of science. The majority of these applications focuses on analyzing the structure of the network...

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Graphical Analysis of German Parliament Voting Pattern

May 17, 2016
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Graphical Analysis of German Parliament Voting Pattern

We use network visualizations to look into the voting patterns in the current German parliament. I downloaded the data here and all figures can be reproduced using the R code available on Github. Missing values, invalid votes, abstention from voting and not showing up for the vote weres coded as (-1), such that all other responses are...

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Interactions between Categorical Variables in Mixed Graphical Models

April 28, 2016
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Interactions between Categorical Variables in Mixed Graphical Models

In a previous post we recovered the conditional independence structure in a dataset of mixed variables describing different aspects of the life of individuals diagnosed with Autism Spectrum Disorder, using the mgm package. While depicting the independence structure in multivariate data set gives a first overview of the relations between variables, in most applications we interested in...

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Estimating mixed graphical models

November 30, 2015
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Determining conditional independence relationships through undirected graphical models is a key component in the statistical analysis of complex obervational data in a wide variety of disciplines. In many situations one seeks to estimate the underlying graphical model of a dataset that includes variables of different domains. As an example, take a typical dataset in the social, behavioral and medical sciences,...

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