Updated README

Author: lindonroberts

README.rst

@@ -1,14 +1,14 @@
-====================================================================================
-DFO-GN: Derivative-Free Nonlinear Least-Squares Solver |Build Status| |PyPI Version|
-====================================================================================
+=====================================================================
+DFO-GN: Derivative-Free Nonlinear Least-Squares Solver |PyPI Version|
+=====================================================================
 DFO-GN is a package for solving nonlinear least-squares minimisation, without requiring derivatives of the objective.
 
 This is an implementation of the algorithm from our paper:
 A Derivative-Free Gauss-Newton  Method, C. Cartis and L. Roberts, submitted (2017).
 
 Documentation
 -------------
-Documentation for DFO-GN is available at [URL].
+See manual.pdf.
 
 Requirements
 ------------
@@ -55,14 +55,6 @@ The source code for DFO-GN is `available on Github <https://https://github.com/n
     $ git clone https://github.com/numericalalgorithmsgroup/dfogn
     $ cd dfogn
 
-or through the `Python Package Index <https://pypi.python.org/pypi/dfogn>`_:
-
- .. code-block:: bash
-
-    $ wget http://pypi.python.org/packages/source/d/dfogn/dfogn-X.X.tar.gz
-    $ tar -xzvf dfogn-X.X.tar.gz
-    $ cd dfogn-X.X
-
 DFO-GN is written in pure Python and requires no compilation. It can be installed using:
 
  .. code-block:: bash
@@ -85,9 +77,7 @@ If you installed DFO-GN manually, you can test your installation by running:
 
     $ python setup.py test
 
-Alternatively, the HTML documentation provides some simple examples of how to run DFO-GN.
+Alternatively, the documentation provides some simple examples of how to run DFO-GN, which are also available in the examples directory.
 
-.. |Build Status| image::  https://travis-ci.org/numericalalgorithmsgroup/DFOGN.svg?branch=master
-                  :target: https://travis-ci.org/numericalalgorithmsgroup/DFOGN
 .. |PyPI Version| image:: https://img.shields.io/pypi/v/DFOGN.svg
-                  :target: https://pypi.python.org/pypi/DFOGN
+                  :target: https://pypi.python.org/pypi/DFOGN