minor

README.md

@@ -3,12 +3,19 @@ AffineInvariantMCMC (aka Emcee): Bayesian sampling using Goodman & Weare's Affin
 
 [![AffineInvariantMCMC](http://pkg.julialang.org/badges/AffineInvariantMCMC_0.4.svg)](http://pkg.julialang.org/?pkg=AffineInvariantMCMC&ver=0.4) [![AffineInvariantMCMC](http://pkg.julialang.org/badges/AffineInvariantMCMC_0.5.svg)](http://pkg.julialang.org/?pkg=AffineInvariantMCMC&ver=0.5)
 
-[![Build Status](https://travis-ci.org/madsjulia/AffineInvariantMCMC.jl.svg?branch=master)](https://travis-ci.org/madsjulia/Mads.jl)
+[![Build Status](https://travis-ci.org/madsjulia/AffineInvariantMCMC.jl.svg?branch=master)](https://travis-ci.org/madsjulia/AffineInvariantMCMC.jl)
 
 [![Coverage Status](https://coveralls.io/repos/madsjulia/AffineInvariantMCMC.jl/badge.svg?branch=master)](https://coveralls.io/r/madsjulia/AffineInvariantMCMC.jl?branch=master)
 
 AffineInvariantMCMC (aka Emcee) is a module of MADS.
 
+Reference:
+
+Goodman, Jonathan, and Jonathan Weare. "Ensemble samplers with affine invariance." Communications in applied mathematics and computational science 5.1 (2010): 65-80.
+
+MADS
+====
+
 MADS is an open-source [Julia](http://julialang.org) code designed as an integrated high-performance computational framework performing a wide range of model-based analyses:
 
 * Sensitivity Analysis