updating README

README.Rmd

@@ -12,7 +12,7 @@ knitr::opts_chunk$set(echo = TRUE)
 [![AppVeyor build status](https://ci.appveyor.com/api/projects/status/github/jchiquet/missSBM?branch=master&svg=true)](https://ci.appveyor.com/project/jchiquet/missSBM)
 [![Coverage status](https://codecov.io/gh/jchiquet/missSBM/branch/master/graph/badge.svg)](https://codecov.io/github/jchiquet/missSBM?branch=master)
 
-> When a network is partially observed (here, missing dyads, that is, entries with NAs in the adjacency matrix rather than 1 or 0), it is possible to account for the underlying process that generates those NAs. missSBM adjusts the popular Stochastic Block Model from network data sampled under various missing data conditions, as described in [10.1080/01621459.2018.1562934](https://doi.org/10.1080/01621459.2018.1562934).
+> When a network is partially observed (here, NAs in the adjacency matrix rather than 1 or 0  due to missing information between node pairs), it is possible to account for the underlying process that generates those NAs. 'missSBM' adjusts the popular stochastic block model from network data  sampled under various missing data conditions, as described in Tabouy, Barbillon and Chiquet (2019) [10.1080/01621459.2018.1562934](https://doi.org/10.1080/01621459.2018.1562934).
 
 ## Installation
 

README.md

@@ -8,12 +8,13 @@ status](https://ci.appveyor.com/api/projects/status/github/jchiquet/missSBM?bran
 [![Coverage
 status](https://codecov.io/gh/jchiquet/missSBM/branch/master/graph/badge.svg)](https://codecov.io/github/jchiquet/missSBM?branch=master)
 
-> When a network is partially observed (here, missing dyads, that is,
-> entries with NA in the adjacency matrix rather than 1 or 0), it is
-> possible to account for the underlying process that generates those
-> NAs. *missSBM* is an R package for adjusting the popular Stochastic
-> Block Models from network data sampled under various missing data
-> conditions.
+> When a network is partially observed (here, NAs in the adjacency
+> matrix rather than 1 or 0 due to missing information between node
+> pairs), it is possible to account for the underlying process that
+> generates those NAs. ‘missSBM’ adjusts the popular stochastic block
+> model from network data sampled under various missing data conditions,
+> as described in Tabouy, Barbillon and Chiquet (2019)
+> [10.1080/01621459.2018.1562934](https://doi.org/10.1080/01621459.2018.1562934).
 
 ## Installation