diff --git a/DESCRIPTION b/DESCRIPTION
index 50ddd60..68cb016 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -4,9 +4,8 @@ Version: 0.1.0
 Authors@R: c(
     person("Nan", "Xiao", email = "me@nanx.me", role = c("aut", "cre", "cph"),
            comment = c(ORCID = "0000-0002-0250-5673")))
-Description: A minimalist implementation of model stacking
-    by Wolpert (1992) <doi:10.1016/S0893-6080(05)80023-1>
-    for boosted tree models.
+Description: A minimalist implementation of model stacking by
+    Wolpert (1992) <doi:10.1016/S0893-6080(05)80023-1> for boosted tree models.
     A classic, two-layer stacking model is implemented, where the first layer
     generates features using gradient boosting trees, and the second layer
     employs a logistic regression model that uses these features as inputs.
diff --git a/README.md b/README.md
index 558cb3c..126e20d 100644
--- a/README.md
+++ b/README.md
@@ -13,13 +13,21 @@ and catboost ([Prokhorenkova et al., 2018](https://dl.acm.org/doi/abs/10.5555/33
 
 ## Installation
 
-Install from GitHub:
+The easiest way to get stackgbm is to install from CRAN:
 
 ```r
+install.packages("stackgbm")
+```
+
+Alternatively, to use a new feature or get a bug fix,
+you can install the development version of stackgbm from GitHub:
+
+```r
+# install.packages("remotes")
 remotes::install_github("nanxstats/stackgbm")
 ```
 
-To install all dependencies, check out the instructions from
+To install all potential dependencies, check out the instructions from
 [manage dependencies](https://github.com/nanxstats/stackgbm/wiki/Manage-dependencies).
 
 ## Model