add reference for mcmc samples

DESCRIPTION

@@ -5,8 +5,9 @@ Authors@R:
   person("Joe", "Thorley", role = c("aut", "cre"), email = "[email protected]", comment = c(ORCID = "0000-0002-7683-4592"))
 Description: Generates derived parameter(s) from Monte Carlo Markov Chain (MCMC) 
     samples using R code. This allows Bayesian models to be fitted without the 
-    inclusion of derived parameters which add unnecessary complexity and 
-    slow model fitting.
+    inclusion of derived parameters which add unnecessary clutter and 
+    slow model fitting. For more information on MCMC samples see 
+    Brooks et al. (2011) <isbn:978-1-4200-7941-8>.
 License: MIT + file LICENSE
 Depends:
     R (>= 3.4.0)
@@ -22,8 +23,6 @@ Suggests:
     plyr,
     doParallel,
     testthat
-Remotes:
-    poissonconsulting/mcmcr
 URL: https://github.com/poissonconsulting/mcmcderive
 BugReports: https://github.com/poissonconsulting/mcmcderive/issues
 Encoding: UTF-8

README.Rmd

@@ -26,7 +26,8 @@ knitr::opts_chunk$set(
 ## Why `mcmcderive`?
 
 `mcmcderive` is an R package to generate derived parameter(s) from Monte Carlo Markov Chain (MCMC) samples using R code.
-This is useful because it means Bayesian models can be fitted without the inclusion of derived parameters which add unnecessary complexity and slow model fitting.
+This is useful because it means Bayesian models can be fitted without the inclusion of derived parameters which add unnecessary clutter and slow model fitting.
+For more information on MCMC samples see Brooks et al. (2011)
 
 ### Parallel Chains
 
@@ -77,3 +78,7 @@ Please report any [issues](https://github.com/poissonconsulting/mcmcderive/issue
 
 Please note that the 'mcmcderive' project is released with a [Contributor Code of Conduct](https://poissonconsulting.github.io/mcmcderive/CODE_OF_CONDUCT.html).
 By contributing to this project, you agree to abide by its terms.
+
+## References
+
+Brooks, S., Gelman, A., Jones, G.L., and Meng, X.-L. (Editors). 2011. Handbook for Markov Chain Monte Carlo. Taylor & Francis, Boca Raton.

README.md

@@ -23,7 +23,8 @@ status](https://www.r-pkg.org/badges/version/mcmcderive)](https://cran.r-project
 `mcmcderive` is an R package to generate derived parameter(s) from Monte
 Carlo Markov Chain (MCMC) samples using R code. This is useful because
 it means Bayesian models can be fitted without the inclusion of derived
-parameters which add unnecessary complexity and slow model fitting.
+parameters which add unnecessary clutter and slow model fitting. For
+more information on MCMC samples see Brooks et al. (2011)
 
 ### Parallel Chains
 
@@ -113,3 +114,8 @@ Please note that the ‘mcmcderive’ project is released with a
 [Contributor Code of
 Conduct](https://poissonconsulting.github.io/mcmcderive/CODE_OF_CONDUCT.html).
 By contributing to this project, you agree to abide by its terms.
+
+## References
+
+Brooks, S., Gelman, A., Jones, G.L., and Meng, X.-L. (Editors). 2011.
+Handbook for Markov Chain Monte Carlo. Taylor & Francis, Boca Raton.