Add content to the front page of the docs.

Author: arokem

docs/source/index.rst

@@ -1,10 +1,28 @@
 
-`fracridge` : Ridge regression with fraction regularization
-============================================================
-
-This software automatically finds regularization metaparameters for ridge
-regression
-
+`fracridge` : fractional ridge regression
+=========================================
+
+Ridge regression (RR) is a regularization technique that penalizes the L2-norm
+of the coefficients in linear regression. One of the challenges of using RR is
+the need to set a hyperparameter (α) that controls the amount of regularization.
+Cross-validation is typically used to select the best α from a set of
+candidates. However, efficient and appropriate selection of α can be
+challenging, particularly where large amounts of data are analyzed. Because the
+selected α depends on the scale of the data and predictors, it is also not
+straightforwardly interpretable.
+
+Here, we reparameterize RR in terms of the ratio γ between the L2-norms of the
+regularized and unregularized coefficients.
+
+This approach, called fractional RR (FRR), has several benefits:
+the solutions obtained for different γ are guaranteed to vary, guarding against
+wasted calculations, and automatically span the relevant range of
+regularization, avoiding the need for arduous manual exploration.
+
+In a `companion preprint article <https://arxiv.org/abs/2005.03220>`_, we show
+that the proposed method is fast and scalable for large-scale data problems, and
+delivers results that are straightforward to interpret and compare across models
+and datasets.
 
 .. toctree::
    :maxdepth: 2
@@ -19,5 +37,3 @@ Indices and tables
 * :ref:`genindex`
 * :ref:`modindex`
 * :ref:`search`
-
-