Minor grammar fix. Added references.

AEBilgrau · Mar 29, 2016 · b87a489 · b87a489
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diff --git a/R/GMCM-package.R b/R/GMCM-package.R
@@ -33,6 +33,12 @@
 #'   Maintainer: Anders Ellern Bilgrau <anders.ellern.bilgrau@@gmail.com>
 #' @docType package
 #' @references
+#'   Anders Ellern Bilgrau, Poul Svante Eriksen, Jakob Gulddahl Rasmussen,
+#'   Hans Erik Johnsen, Karen Dybkaer, Martin Boegsted (2016). GMCM:
+#'   Unsupervised Clustering and Meta-Analysis Using Gaussian Mixture Copula
+#'   Models. Journal of Statistical Software, 70(2), 1-23.
+#'   doi:10.18637/jss.v070.i02
+#'
 #'   Li, Q., Brown, J. B. J. B., Huang, H., & Bickel, P. J. (2011).
 #'   Measuring reproducibility of high-throughput experiments. The Annals of
 #'   Applied Statistics, 5(3), 1752-1779. doi:10.1214/11-AOAS466

diff --git a/README.md b/README.md
@@ -12,7 +12,8 @@ Gaussian copula mixture models (GMCMs) are a very flexible alternative to gaussi
 
 The optimization of the complicated likelihood function is difficult, however. The **GMCM** package utilizes [**Rcpp**](https://github.com/RcppCore/Rcpp) and [**RcppArmadillo**](https://github.com/RcppCore/RcppArmadillo) to evaluate the likelihood function quickly and arrive at a parameter estimate using various standard numerical optimization routines.
 
-Additional information and documentation can be found by running `help(package = "GMCM")` in R for help and examples.
+Additional information, documentation, help, and examples can be found by running `help(package = "GMCM")`  or `?GMCM` in **R**. 
+The paper [1] is also found as a vignette by `vignette("GMCM-JStatSoft")`.
 The core user functions of **GMCM** are `fit.full.GMCM` and `fit.meta.GMCM`.
 
 ## Installation
@@ -40,10 +41,10 @@ For previous versions of **GMCM**, visit the old [releases at GitHub](https://gi
 
 ## References
 
- * Anders Ellern Bilgrau, Poul Svante Eriksen, Jakob Gulddahl Rasmussen, Hans 
-   Erik Johnsen, Karen Dybkaer, Martin Boegsted (2016). **GMCM: Unsupervised 
-   Clustering and Meta-Analysis Using Gaussian Mixture Copula Models.** 
-   Journal of Statistical Software, 70(2), 1-23. doi:10.18637/jss.v070.i02
+  1. Anders Ellern Bilgrau, Poul Svante Eriksen, Jakob Gulddahl Rasmussen, Hans 
+     Erik Johnsen, Karen Dybkaer, Martin Boegsted (2016). **GMCM: Unsupervised 
+     Clustering and Meta-Analysis Using Gaussian Mixture Copula Models.** 
+     Journal of Statistical Software, 70(2), 1-23. doi:10.18637/jss.v070.i02
 
 ## Usage
 ### Meta Analysis example

diff --git a/man/GMCM-package.Rd b/man/GMCM-package.Rd
@@ -77,7 +77,13 @@ Anders Ellern Bilgrau,
   Maintainer: Anders Ellern Bilgrau <anders.ellern.bilgrau@gmail.com>
 }
 \references{
-Li, Q., Brown, J. B. J. B., Huang, H., & Bickel, P. J. (2011).
+Anders Ellern Bilgrau, Poul Svante Eriksen, Jakob Gulddahl Rasmussen,
+  Hans Erik Johnsen, Karen Dybkaer, Martin Boegsted (2016). GMCM:
+  Unsupervised Clustering and Meta-Analysis Using Gaussian Mixture Copula
+  Models. Journal of Statistical Software, 70(2), 1-23.
+  doi:10.18637/jss.v070.i02
+
+  Li, Q., Brown, J. B. J. B., Huang, H., & Bickel, P. J. (2011).
   Measuring reproducibility of high-throughput experiments. The Annals of
   Applied Statistics, 5(3), 1752-1779. doi:10.1214/11-AOAS466