diff --git a/src/distribution/mod.rs b/src/distribution/mod.rs
index 514132ff..e6a2fd92 100644
--- a/src/distribution/mod.rs
+++ b/src/distribution/mod.rs
@@ -290,9 +290,10 @@ pub trait ContinuousMultivariateCDF<K: Float, T: Float> {
     ///
     /// ```
     /// use statrs::distribution::{ContinuousMultivariateCDF, MultivariateNormal};
+    /// use nalgebra::DVector;
     ///
     /// let mvn = MultivariateNormal::new(vec![0., 0.], vec![1., 0., 0., 1.]).unwrap();
-    /// assert_eq!(0.25, mvn.cdf([0., 0.,]));
+    /// assert_eq!(0.25, mvn.cdf(DVector::from_vec(vec![0., 0.,])));
     /// ```
     fn cdf(&self, x: DVector<K>) -> T;
 
@@ -304,9 +305,10 @@ pub trait ContinuousMultivariateCDF<K: Float, T: Float> {
     ///
     /// ```
     /// use statrs::distribution::{ContinuousMultivariateCDF, MultivariateNormal};
+    /// use nalgebra::DVector;
     ///
     /// let mvs = MultivariateNormal::new(vec![0., 0.], vec![1., 0., 0., 1.]).unwrap();
-    /// assert_eq!(f64::NEG_INFINITY, mvs.sf([f64::INFINITY, f64::INFINITY]));
+    /// assert_eq!(0., mvs.sf(DVector::from_vec(vec![f64::INFINITY, f64::INFINITY])));
     /// ```
     fn sf(&self, x: DVector<K>) -> T;
 }
diff --git a/src/distribution/multivariate_normal.rs b/src/distribution/multivariate_normal.rs
index 58a41c12..6cb2f52a 100644
--- a/src/distribution/multivariate_normal.rs
+++ b/src/distribution/multivariate_normal.rs
@@ -273,6 +273,7 @@ impl ContinuousMultivariateCDF<f64, f64> for MultivariateNormal {
     /// multivariate normal distribution, using approximation with
     /// `N` points.
     fn sf(&self, x: DVector<f64>) -> f64 {
+        // Shift integration limit wrt. mean
         1. - self.cdf(x)
     }
 }
diff --git a/src/distribution/multivariate_uniform.rs b/src/distribution/multivariate_uniform.rs
index 97921cba..c5946499 100644
--- a/src/distribution/multivariate_uniform.rs
+++ b/src/distribution/multivariate_uniform.rs
@@ -12,11 +12,12 @@ use std::f64;
 ///
 /// ```
 /// use statrs::distribution::{MultivariateUniform, Continuous};
-/// use statrs::statistics::Distribution;
+/// use statrs::statistics::{Distribution, MeanN};
+/// use nalgebra::DVector;
 ///
 /// let n = MultivariateUniform::new(vec![-1., 0.], vec![0., 1.]).unwrap();
-/// assert_eq!(n.mean().unwrap(), DVector::from_vec(vec![-0.5, 0.5]);
-/// assert_eq!(n.pdf(DVector::from_vec(vec![-0.5, 0.5])), 1.);
+/// assert_eq!(n.mean().unwrap(), DVector::from_vec(vec![-0.5, 0.5]));
+/// assert_eq!(n.pdf(&DVector::from_vec(vec![-0.5, 0.5])), 1.);
 /// ```
 #[derive(Debug, Clone, PartialEq)]
 pub struct MultivariateUniform {
@@ -40,11 +41,12 @@ impl MultivariateUniform {
     /// use statrs::distribution::MultivariateUniform;
     /// use std::f64;
     ///
-    /// let mut result = Uniform::new(vec![-1., 0.], vec![0., 1.,]);
+    /// let mut result = MultivariateUniform::new(vec![-1., 0.], vec![0., 1.,]);
     /// assert!(result.is_ok());
     ///
-    /// result = Uniform::new(f64::NAN, f64::NAN);
-    /// result = Uniform::new(vec![0., f64::NAN], vec![f64::NAN, 1.]);
+    /// result = MultivariateUniform::new(vec![f64::NAN], vec![f64::NAN]);
+    /// assert!(result.is_err());
+    /// result = MultivariateUniform::new(vec![0., f64::NAN], vec![f64::NAN, 1.]);
     /// assert!(result.is_err());
     /// ```
     pub fn new(min: Vec<f64>, max: Vec<f64>) -> Result<MultivariateUniform> {