diff -ruN src/main/java/com/tdunning/math/stats/ArrayDigest.java src/main/java/com/tdunning/math/stats/ArrayDigest.java
--- src/main/java/com/tdunning/math/stats/ArrayDigest.java	2014-05-13 05:05:45.000000000 +0200
+++ src/main/java/com/tdunning/math/stats/ArrayDigest.java	2015-07-13 09:16:26.231915177 +0200
@@ -26,7 +26,7 @@
 
 /**
  * Array based implementation of a TDigest.
- * <p/>
+ * <br>
  * This implementation is essentially a one-level b-tree in which nodes are collected into
  * pages typically with 32 values per page.  Commonly, an ArrayDigest contains 500-3000
  * centroids.  With 32 values per page, we have about 32 values per page and about 30 pages
@@ -394,7 +394,7 @@
     }
 
     /**
-     * Returns a cursor pointing to the first element <= x.  Exposed only for testing.
+     * Returns a cursor pointing to the first element &lt;= x.  Exposed only for testing.
      * @param x The value used to find the cursor.
      * @return The cursor.
      */
@@ -418,7 +418,7 @@
     }
 
     /**
-     * Returns an iterator which will give each element <= to x in non-increasing order.
+     * Returns an iterator which will give each element &lt;= to x in non-increasing order.
      *
      * @param x The upper bound of all returned elements
      * @return An iterator that returns elements in non-increasing order.
diff -ruN src/main/java/com/tdunning/math/stats/AVLTreeDigest.java src/main/java/com/tdunning/math/stats/AVLTreeDigest.java
--- src/main/java/com/tdunning/math/stats/AVLTreeDigest.java	2014-05-13 05:05:45.000000000 +0200
+++ src/main/java/com/tdunning/math/stats/AVLTreeDigest.java	2015-07-13 09:17:02.072307855 +0200
@@ -234,7 +234,7 @@
 
     /**
      * @param q The quantile desired.  Can be in the range [0,1].
-     * @return The minimum value x such that we think that the proportion of samples is <= x is q.
+     * @return The minimum value x such that we think that the proportion of samples is &lt;= x is q.
      */
     @Override
     public double quantile(double q) {
diff -ruN src/main/java/com/tdunning/math/stats/TDigest.java src/main/java/com/tdunning/math/stats/TDigest.java
--- src/main/java/com/tdunning/math/stats/TDigest.java	2014-05-13 05:05:45.000000000 +0200
+++ src/main/java/com/tdunning/math/stats/TDigest.java	2015-07-13 09:19:06.591672123 +0200
@@ -21,21 +21,21 @@
 
 /**
  * Adaptive histogram based on something like streaming k-means crossed with Q-digest.
- * <p/>
+ * <br>
  * The special characteristics of this algorithm are:
- * <p/>
+ * <br>
  * a) smaller summaries than Q-digest
- * <p/>
+ * <br>
  * b) works on doubles as well as integers.
- * <p/>
- * c) provides part per million accuracy for extreme quantiles and typically <1000 ppm accuracy for middle quantiles
- * <p/>
+ * <br>
+ * c) provides part per million accuracy for extreme quantiles and typically &lt;1000 ppm accuracy for middle quantiles
+ * <br>
  * d) fast
- * <p/>
+ * <br>
  * e) simple
- * <p/>
- * f) test coverage > 90%
- * <p/>
+ * <br>
+ * f) test coverage &gt; 90%
+ * <br>
  * g) easy to adapt for use with map-reduce
  */
 public abstract class TDigest {
@@ -91,10 +91,10 @@
     /**
      * Re-examines a t-digest to determine whether some centroids are redundant.  If your data are
      * perversely ordered, this may be a good idea.  Even if not, this may save 20% or so in space.
-     * <p/>
+     * <br>
      * The cost is roughly the same as adding as many data points as there are centroids.  This
-     * is typically < 10 * compression, but could be as high as 100 * compression.
-     * <p/>
+     * is typically &lt; 10 * compression, but could be as high as 100 * compression.
+     * <br>
      * This is a destructive operation that is not thread-safe.
      */
     public abstract void compress();
@@ -107,7 +107,7 @@
     public abstract long size();
 
     /**
-     * Returns the fraction of all points added which are <= x.
+     * Returns the fraction of all points added which are &lt;= x.
      */
     public abstract double cdf(double x);
 
diff -ruN src/main/java/com/tdunning/math/stats/TreeDigest.java src/main/java/com/tdunning/math/stats/TreeDigest.java
--- src/main/java/com/tdunning/math/stats/TreeDigest.java	2014-05-13 05:05:45.000000000 +0200
+++ src/main/java/com/tdunning/math/stats/TreeDigest.java	2015-07-13 09:18:30.988282043 +0200
@@ -26,21 +26,21 @@
 
 /**
  * Adaptive histogram based on something like streaming k-means crossed with Q-digest.
- * <p/>
+ * <br>
  * The special characteristics of this algorithm are:
- * <p/>
+ * <br>
  * a) smaller summaries than Q-digest
- * <p/>
+ * <br>
  * b) works on doubles as well as integers.
- * <p/>
- * c) provides part per million accuracy for extreme quantiles and typically <1000 ppm accuracy for middle quantiles
- * <p/>
+ * <br>
+ * c) provides part per million accuracy for extreme quantiles and typically &lt;1000 ppm accuracy for middle quantiles
+ * <br>
  * d) fast
- * <p/>
+ * <br>
  * e) simple
- * <p/>
- * f) test coverage > 90%
- * <p/>
+ * <br>
+ * f) test coverage &gt; 90%
+ * <br>
  * g) easy to adapt for use with map-reduce
  */
 public class TreeDigest extends AbstractTDigest {
@@ -232,7 +232,7 @@
 
     /**
      * @param q The quantile desired.  Can be in the range [0,1].
-     * @return The minimum value x such that we think that the proportion of samples is <= x is q.
+     * @return The minimum value x such that we think that the proportion of samples is &lt;= x is q.
      */
     @Override
     public double quantile(double q) {