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Dear All,

There are some seats available for the Sunbelt 2019 workshop on: "Exploring
networks using latent variable models in R with lvm4net" that will take
place on Tuesday at 3:00PM. Those already registered to the Sunbelt
Conference will be able to add this workshop to their order by connecting
on the platform with the email address they used to register. Link to
registration: https://urldefense.proofpoint.com/v2/url?u=https-3A__www.fourwav.es_view_717_registration_&d=DwIBaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=RNel6SnBADhBbHo_2Iu3L7gHlBsjChh3Acf_Cxjzedg&s=kkIZHB46dqsR8FSObPpU_-rno9rTgI1lcq57koRwEVQ&e= 

Topics of this hands-on workshop include: latent space models for one-mode,
two-mode, and multiplex networks and model-based clustering for two-mode
networks.

For more details on the package and the models available you can see:
https://urldefense.proofpoint.com/v2/url?u=http-3A__igollini.github.io_lvm4net_&d=DwIBaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=RNel6SnBADhBbHo_2Iu3L7gHlBsjChh3Acf_Cxjzedg&s=vl-vW8bY2wbr399zMdW-c4Xh4PPKqBeLxY8YUCRq4DQ&e= 

Best wishes,

Isabella Gollini

Latent variable network models represent an effective and efficient
approach for exploring the structure of complex relational data. In this
hands-on workshop we will describe and demonstrate the modelling approaches
of the lvm4net package for R by the analysis of real network data. This
package have been developed to provide a rich source of insights on
probabilistic visualisation and clustering and describing the heterogenous
connectivity structure of one-mode, two-mode, and multiplex networks using
fast estimation techniques (such as variational inference).

Topics of the workshop include:
- Introduction to latent variable network models;
- Latent space models for one-mode, two-mode, and multiplex networks;
- Model-based clustering for two-mode networks;
- Probabilistic visualisation and interpretation of estimated latent
variables;
- Model selection and goodness of fit assessment.

Prerequisites: Basic knowledge of network analysis, statistics and R.
Participants are recommended to bring a laptop with R/RStudio, and the
latest version of lvm4net installed.

The package version 0.3 of lvm4net is now available on GitHub at
https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_igollini_lvm4net&d=DwIBaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=RNel6SnBADhBbHo_2Iu3L7gHlBsjChh3Acf_Cxjzedg&s=s3PR6k2pj0NInh9LCsxx_PbrnIZQH2L3awD-L8_JnTU&e=  and will be available on CRAN very soon
at https://urldefense.proofpoint.com/v2/url?u=https-3A__CRAN.R-2Dproject.org_package-3Dlvm4net&d=DwIBaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=RNel6SnBADhBbHo_2Iu3L7gHlBsjChh3Acf_Cxjzedg&s=Zb4xQwGcI3FrFf77RZthL2Rzo3vh0yCizrvPqsbg-4Y&e= , and on GitHub. Further
information about the package are available at
https://urldefense.proofpoint.com/v2/url?u=http-3A__igollini.github.io_lvm4net_&d=DwIBaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=RNel6SnBADhBbHo_2Iu3L7gHlBsjChh3Acf_Cxjzedg&s=vl-vW8bY2wbr399zMdW-c4Xh4PPKqBeLxY8YUCRq4DQ&e= .

-- 
Isabella Gollini

Assistant Professor in Statistics
School of Mathematics and Statistics,
University College Dublin, Ireland
https://urldefense.proofpoint.com/v2/url?u=https-3A__people.ucd.ie_isabella.gollini&d=DwIBaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=RNel6SnBADhBbHo_2Iu3L7gHlBsjChh3Acf_Cxjzedg&s=prrhA94jVsR5rCiWJYpHCRJnePUvfiwNcy_l9VAj9qo&e= 
@IsabellaGollini

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