better pkgdown template plus a bunch of typography fixes

.Rbuildignore

@@ -13,3 +13,5 @@
 ^docs$
 ^_pkgdown\.yml$
 ^build_test_models.R$
+^pkgdown/.*$
+^pkgdown$

README.Rmd

@@ -1,4 +1,6 @@
 ---
+author: "Matthew Kay"
+date: "`r Sys.Date()`"
 output: 
   github_document:
     df_print: kable
@@ -8,8 +10,6 @@ output:
 
 [![Build Status](https://travis-ci.org/mjskay/tidybayes.png?branch=master)](https://travis-ci.org/mjskay/tidybayes)
 
-_Matthew Kay, University of Michigan, <mjskay@umich.edu>_
-
 ![Preview of tidybayes plots](man/figures/preview.png)
 
 [Tidy](http://cran.r-project.org/web/packages/tidyr/vignettes/tidy-data.html)
@@ -328,7 +328,7 @@ m %>%
 This plot shows 66% and 95% quantile credible intervals of posterior mean for each condition (point + black line); 95%, 80%, and 50% posterior predictive intervals (blue); and the data.
 
 
-#### Fit curves
+### Fit curves
 
 For models that support it (like `rstanarm` and `brms` models), We can also use the `add_fitted_samples` or `add_predicted_samples` functions to generate posterior fits or predictions. Combined with the functions from the `modelr` package, this makes it easy to generate fit curves.
 

README.md

@@ -1,11 +1,11 @@
+Matthew Kay
+2017-11-26
 
 tidybayes: Bayesian analysis + tidy data + geoms
 ================================================
 
 [![Build Status](https://travis-ci.org/mjskay/tidybayes.png?branch=master)](https://travis-ci.org/mjskay/tidybayes)
 
-*Matthew Kay, University of Michigan, <mjskay@umich.edu>*
-
 ![Preview of tidybayes plots](man/figures/preview.png)
 
 [Tidy](http://cran.r-project.org/web/packages/tidyr/vignettes/tidy-data.html) data frames (one observation per row) are particularly convenient for use in a variety of R data manipulation and visualization packages. However, when using MCMC / Bayesian samplers like JAGS or Stan in R, we often have to translate this data into a form the sampler understands, and then after running the model, translate the resulting sample into a more tidy format for use with other R functions. `tidybayes` aims to simplify these two common (often tedious) operations:
@@ -297,7 +297,7 @@ m %>%
 
 This plot shows 66% and 95% quantile credible intervals of posterior mean for each condition (point + black line); 95%, 80%, and 50% posterior predictive intervals (blue); and the data.
 
-#### Fit curves
+### Fit curves
 
 For models that support it (like `rstanarm` and `brms` models), We can also use the `add_fitted_samples` or `add_predicted_samples` functions to generate posterior fits or predictions. Combined with the functions from the `modelr` package, this makes it easy to generate fit curves.
 

_pkgdown.yml

@@ -2,7 +2,7 @@ url: http://mjskay.github.io/tidybayes
 
 template:
   params:
-    bootswatch: cerulean
+    bootswatch: paper
     ganalytics: UA-93322-5
 
 authors:

docs/extra.css

@@ -0,0 +1,68 @@
+body {
+  font-size: 15.5px;
+}
+
+.navbar-brand {
+  font-size: 16px;
+  font-weight: bold;
+}
+
+.navbar-default .navbar-nav>li>a:hover,
+.navbar-default .navbar-nav>li>a:focus {
+  background-color: #eee;
+}
+
+p.caption {
+  display: none;
+}
+
+h1, .h1 {
+  font-size: 36px;
+  font-weight: bold;
+}
+
+h1 small, .h1 small {
+  font-size: 70%;
+  text-transform: uppercase;
+  letter-spacing: 0.5px;
+}
+
+h2, .h2 {
+  font-size: 28px;
+  font-weight: bold;
+}
+
+h3, .h3 {
+  font-size: 20px;
+  font-weight: bold;
+}
+
+h4, .h4 {
+  font-size: 20px;
+  font-weight: normal;
+}
+
+.contents h1, .contents h2, .contents h3, .contents h4 {
+  margin-top: -40px;
+  margin-bottom: 20px;
+}
+
+.contents .page-header h1 {
+  margin-top: -60px;
+}
+
+.contents h3, .contents h4 {
+  margin-top: -60px;
+}
+
+h4.date, h4.author {
+  font-size: 1em;
+  color: #bbb;
+  display: inline;
+  padding-right: 0.5em;
+}
+
+pre code {
+  font-size: 13.5px;
+  white-space: pre;
+}