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AUEB Stats Seminars 15/10/2021: Statistical Network Analysis with Bergm by Lampros Bouranis (AUEB) Forumgrstats

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Λέσχη Φίλων Στατιστικής - GrStats forum
AUEB Stats Seminars 15/10/2021: Statistical Network Analysis with Bergm by Lampros Bouranis (AUEB) Forumgrstats
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AUEB Stats Seminars 15/10/2021: Statistical Network Analysis with Bergm by Lampros Bouranis (AUEB) Empty Re: AUEB Stats Seminars 15/10/2021: Statistical Network Analysis with Bergm by Lampros Bouranis (AUEB)

Wed 20 Oct 2021 - 18:13
Το βίντεο της ομιλίας είναι τώρα διαθέσιμο στο youtube κανάλι του Τμήματος Στατιστικής του ΟΠΑ https://youtu.be/w40VznLKKhg

The video of the talk is now available at the youtube channel of the Department of Statistics https://youtu.be/w40VznLKKhg
grstats
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Join date : 2009-10-21
http://stat-athens.aueb.gr/~grstats/

AUEB Stats Seminars 15/10/2021: Statistical Network Analysis with Bergm by Lampros Bouranis (AUEB) Empty AUEB Stats Seminars 15/10/2021: Statistical Network Analysis with Bergm by Lampros Bouranis (AUEB)

Wed 20 Oct 2021 - 18:12
AUEB Stats Seminars 15/10/2021: Statistical Network Analysis with Bergm by Lampros Bouranis (AUEB) 2122_a12


Presenter:  Lampros Bouranis
Research Fellow, Department of Statistics, AUEB

Date: Friday 15/10/2021, 12:30

Title: Statistical Network Analysis with Bergm

Abstract: Recent advances in computational methods for intractable models have made network data increasingly amenable to statistical analysis. Exponential random graph models (ERGMs) emerged as one of the main families of models capable of capturing the complex dependence structure of network data in a wide range of applied contexts. The Bergm package for R has become a popular package to carry out Bayesian parameter inference, missing data imputation, model selection and goodness-of-fit diagnostics for ERGMs. Over the last few years, the package has been considerably improved in terms of efficiency by adopting some of the state-of-the-art Bayesian computational methods for doubly-intractable distributions. Recently, version 5 of the package has been made available on CRAN having undergone a substantial makeover, which has made it more accessible and easier to use for practitioners. New functions include data augmentation procedures based on the approximate exchange algorithm for dealing with missing data, adjusted pseudo-likelihood and pseudo-posterior procedures, which allow for fast approximate inference of the ERGM parameter posterior and model evidence for networks on several thousands nodes. This is joint work with Alberto Caimo (Technological University Dublin), Robert Krause (Free University of Berlin) and Nial Friel (University College Dublin).
arXiv: https://arxiv.org/abs/2104.02444
CRAN: https://CRAN.R-project.org/package=Bergm

Meeting Link: https://teams.microsoft.com/l/meetup-join/19%3a0fe3bd7e094a4ccfacecb92ce36cfe69%40thread.tacv2/1629962232332?context=%7b%22Tid%22%3a%22ad5ba4a2-7857-4ea1-895e-b3d5207a174f%22%2c%22Oid%22%3a%22381c5dc1-ed77-403a-9d53-e2db51c33563%22%7d


Last edited by grstats on Wed 20 Oct 2021 - 18:14; edited 1 time in total
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