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BLSM  

Bayesian Latent Space Model
View on CRAN: Click here


Download and install BLSM package within the R console
Install from CRAN:
install.packages("BLSM")

Install from Github:
library("remotes")
install_github("cran/BLSM")

Install by package version:
library("remotes")
install_version("BLSM", "0.1.0")



Attach the package and use:
library("BLSM")
Maintained by
Alberto Donizetti
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-04-26
Latest Update: 2018-04-26
Description:
Provides a Bayesian latent space model for complex networks, either weighted or unweighted. Given an observed input graph, the estimates for the latent coordinates of the nodes are obtained through a Bayesian MCMC algorithm. The overall likelihood of the graph depends on a fundamental probability equation, which is defined so that ties are more likely to exist between nodes whose latent space coordinates are close. The package is mainly based on the model by Hoff, Raftery and Handcock (2002) and contains some extra features (e.g., removal of the Procrustean step, weights implemented as coefficients of the latent distances, 3D plots). The original code related to the above model was retrieved from . Users can inspect the MCMC simulation, create and customize insightful graphical representations or apply clustering techniques.
How to cite:
Alberto Donizetti (2018). BLSM: Bayesian Latent Space Model. R package version 0.1.0, https://cran.r-project.org/web/packages/BLSM
Previous versions and publish date:
No previous versions
Other packages that cited BLSM R package
View BLSM citation profile
Other R packages that BLSM depends, imports, suggests or enhances
Functions, R codes and Examples using the BLSM R package
Some associated functions: BLSM . Z_up . alpha_up . dst . estimate_latent_positions . example_adjacency_matrix . example_blsm_obj . example_weights_matrix . lpY . lpYNODE . lpz_dist . lpz_distNODE . mlpY . plot_latent_positions . plot_traceplots_acf . proc_crr . 
Some associated R codes: RcppExports.R . blsm.R . data.R . package.R .  Full BLSM package functions and examples
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