add pkgdown build

.Rbuildignore

@@ -1,3 +1,5 @@
+^docs$
+^_pkgdown\.yml$
 ^data-raw$
 ^.*\.Rproj$
 ^\.Rproj\.user$

README.Rmd

@@ -14,7 +14,7 @@ knitr::opts_chunk$set(
 
 # ungeviz
 
-Tools for visualizing uncertainty with ggplot2, written by Claus O. Wilke
+Tools for visualizing uncertainty with ggplot2.
 
 This package is meant to provide helpful add-on functionality for ggplot2 to 
 visualize uncertainty. The package is particularly focused on hypothetical
@@ -51,27 +51,26 @@ cacao %>% filter(location %in% c("Canada", "U.S.A.")) %>%
   transition_states(.draw, 1, 3)
 ```
 
-Both the bootstrapper and sampler objects can be used for repeated reproducible sampling, by passing the sampe bootstrapper or sampler object as data to multiple ggplot2 layers.
+Both the bootstrapper and sampler objects can be used for repeated reproducible sampling, by passing the same bootstrapper or sampler object as data to multiple ggplot2 layers.
 
 ```{r bluejays-lm-anim, fig.asp = 0.5}
 data(BlueJays, package = "Stat2Data")
 
 # set up bootstrapping object that generates 20 bootstraps
 # and groups by variable `KnownSex`
-bs <- bootstrapper(20, KnownSex)
+bsr <- bootstrapper(20, KnownSex)
 
 ggplot(BlueJays, aes(BillLength, Head, color = KnownSex)) +
   geom_smooth(method = "lm", color = NA) +
   geom_point(alpha = 0.3) +
   # `.row` is a generated column providing a unique row number for all rows
-  geom_point(data = bs, aes(group = .row)) +
-  geom_smooth(data = bs, method = "lm", fullrange = TRUE, se = FALSE) +
+  geom_point(data = bsr, aes(group = .row)) +
+  geom_smooth(data = bsr, method = "lm", fullrange = TRUE, se = FALSE) +
   facet_wrap(~KnownSex, scales = "free_x") +
   scale_color_manual(values = c(F = "#D55E00", M = "#0072B2"), guide = "none") +
   theme_bw() +
   transition_states(.draw, 1, 1) + 
-  enter_fade() + 
-  exit_fade()
+  enter_fade() + exit_fade()
 ```
 
 ## Smooth draws {#smooth-draws}
@@ -81,15 +80,16 @@ Instead of bootstrapping smoothers or regression lines, we can also fit a smooth
 ```{r mtcars-smooth-anim}
 ggplot(mtcars, aes(hp, mpg)) + 
   geom_point() +
-  stat_smooth_draws(times = 20) + 
+  stat_smooth_draws(times = 20, aes(group = stat(.draw))) + 
   theme_bw() +
-  transition_states(stat(.draw), 1, 2)
+  transition_states(stat(.draw), 1, 2) +
+  enter_fade() + exit_fade()
 ```
 
 
-## Confidence strips {#confidence-strips}
+## Miscellaneous geoms and stats {#geoms-stats}
 
-The ungeviz package provides a convenient way of drawing confidence strips, via `stat_confidence_density()`.
+Several geoms and stats are provided that can be helpful when visualizing uncertainty, including `geom_hpline()` and `geom_vpline()` used in the sampling example above, and `stat_confidence_density()` which can draw confidence strips.
 
 ```{r cacao-means}
 library(broom)

_pkgdown.yml

@@ -0,0 +1,30 @@
+destination: docs
+
+reference:
+- title: Sampling and bootstrapping
+  desc: Reliable sampling from and bootstrapping of data frames
+  contents:
+  - bootstrapper
+  - sampler
+
+- title: Posterior draws
+  desc: Posterior draws of GAM fits
+  contents:
+  - stat_smooth_draws
+  - sample_outcomes
+  - confidence_band
+
+- title: Geoms
+  desc: Miscellaneous ggplot2 geoms
+  contents:
+  - starts_with("geom_")
+
+- title: Stats
+  desc: Miscellaneous ggplot2 stats
+  contents:
+  - starts_with("stat_")
+
+- title: Data sets
+  desc: Demo data sets provided with the package
+  contents:
+  - cacao