new readme

README.md

@@ -6,32 +6,34 @@
 # Introduction
 `ghypernet` is an OpenSource R package that allows to estimate and work with Generalised Hypergeometric Ensembles of Random Graphs (gHypEG).
 
-`ghypernet` has been developed specifically for the analysis of large networks characterised by a large number of repeated edges.
+`ghypernet` has been developed specifically for the analysis of networks characterised by a large number of repeated edges.
 It provides efficient methods to perform hypothesis testing and model selection on such data.
 
-The theoretical foundation of this paper, gHypEGs, was developed in the following works:
+Explore the provided Vignettes for some examples on how to analyse networks with `ghypernet`.
 
-  1. Casiraghi, G., Nanumyan, V., Scholtes, I., Schweitzer, F. (2016) [Generalized Hypergeometric Ensembles: Statistical Hypothesis Testing in Complex Networks.](http://arxiv.org/abs/1607.02441) arXiv Prepr. arXiv1607.02441
-  2. Casiraghi, G., Nanumyan, V., Scholtes, I., Schweitzer, F. (2017) [From Relational Data to Graphs: Inferring Significant Links Using Generalized Hypergeometric Ensembles](https://link.springer.com/chapter/10.1007/978-3-319-67256-4_11) in Social Informatics. SocInfo 2017 111-120 (Springer Verlag, 2017). doi:10.1007/978-3-319-67256-4_11
-  3. Casiraghi, G., Nanumyan, V. (2018) [Generalised hypergeometric ensembles of random graphs: the configuration model as an urn problem.](http://arxiv.org/abs/1810.06495)  arXiv Prepr. arXiv1810.06495
-  4. Casiraghi, G. (2018) [Analytical Formulation of the Block-Constrained Configuration Model.](http://arxiv.org/abs/1811.05337)  arXiv Prepr. arXiv1811.05337
+# Installation
+```
+# Install ghypernet from CRAN
+install.packages("ghypernet")
 
+# Or the development version from GitHub:
+devtools::install_github("gi0na/r-ghypernet")
+```
 # Dependencies
 The package uses the library `BiasedUrn` to work with Wallenius' non-central hypergeometric distribution.
 Although this is not required, it is recommended to install the `BiasedUrn` R package, increasing the number of 'colors', i.e., the number of dimensions of the distribution.
 It can be easily done modifying the _makevar_ file.
 In case the `BiasedUrn` library cannot be found, all computations will be performed using the multinomial approximation.
 
-# Installation
-You can install this package directly from GitHub.
-In R, run the following commands to install the package:
-```
-install.packages('devtools')
-devtools::install_github("gi0na/r-ghypernet")
-
-library(ghypernet)
-```
+# References
+The theoretical foundation of the generalised hypergeometric ensemble, gHypEGs, has been developed in the following works:
 
+Casiraghi, G., Nanumyan, V., Scholtes, I., & Schweitzer, F. (2016). [Generalized Hypergeometric Ensembles: Statistical Hypothesis Testing in Complex Networks.](http://arxiv.org/abs/1607.02441) ArXiv Preprint ArXiv:1607.02441.
+Casiraghi, G. (2017). [Multiplex Network Regression: How do relations drive interactions?](http://arxiv.org/abs/1702.02048). ArXiv Preprint ArXiv:1702.02048, 15.
+Casiraghi, G., Nanumyan, V., Scholtes, I., & Schweitzer, F. (2017). [From Relational Data to Graphs: Inferring Significant Links Using Generalized Hypergeometric Ensembles](https://doi.org/10.1007/978-3-319-67256-4_11) (Vol. 10540, pp. 111–120). Springer Verlag.
+Casiraghi, G., & Nanumyan, V. (2018). [Generalised hypergeometric ensembles of random graphs: the configuration model as an urn problem.](http://arxiv.org/abs/1810.06495) ArXiv Preprint ArXiv:1810.06495.
+Casiraghi, G. (2019). [The block-constrained configuration model.](https://doi.org/10.1007/s41109-019-0241-1) Applied Network Science, 4(1), 123. 
+Brandenberger, L., Casiraghi, G., Nanumyan, V., & Schweitzer, F. (2019). [Quantifying triadic closure in multi-edge social networks.](https://doi.org/10.1145/3341161.3342926) Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 307–310.
 
 # Acknowledgements
 The research and development behind `ghypernet` is performed at the Chair of Systems Design, ETH Zürich.