diff --git a/unsafe/src/main/scala/org/apache/spark/sql/daria/functions.scala b/unsafe/src/main/scala/org/apache/spark/sql/daria/functions.scala
index d4322e5..2445065 100644
--- a/unsafe/src/main/scala/org/apache/spark/sql/daria/functions.scala
+++ b/unsafe/src/main/scala/org/apache/spark/sql/daria/functions.scala
@@ -8,9 +8,11 @@ import org.apache.spark.util.Utils
 object functions {
   private def withExpr(expr: Expression): Column = Column(expr)
 
-  def randGamma(seed: Long, shape: Double, scale: Double): Column = withExpr(RandGamma(seed, shape, scale)).alias("gamma_random")
-  def randGamma(shape: Double, scale: Double): Column             = randGamma(Utils.random.nextLong, shape, scale)
-  def randGamma(): Column                                         = randGamma(1.0, 1.0)
+  def randGamma(seed: Long, shape: Double, scale: Double): Column   = withExpr(RandGamma(seed, shape, scale)).alias("gamma_random")
+  def randGamma(seed: Column, shape: Column, scale: Column): Column = withExpr(RandGamma(seed.expr, shape.expr, scale.expr)).alias("gamma_random")
+  def randGamma(shape: Double, scale: Double): Column               = randGamma(Utils.random.nextLong, shape, scale)
+  def randGamma(shape: Column, scale: Column): Column               = randGamma(lit(Utils.random.nextLong), shape, scale)
+  def randGamma(): Column                                           = randGamma(1.0, 1.0)
 
   def randLaplace(seed: Long, mu: Double, beta: Double): Column = {
     val mu_   = lit(mu)
diff --git a/unsafe/src/test/scala/org/apache/spark/sql/daria/functionsTests.scala b/unsafe/src/test/scala/org/apache/spark/sql/daria/functionsTests.scala
index 5147c13..b529c1e 100644
--- a/unsafe/src/test/scala/org/apache/spark/sql/daria/functionsTests.scala
+++ b/unsafe/src/test/scala/org/apache/spark/sql/daria/functionsTests.scala
@@ -27,6 +27,28 @@ object functionsTests extends TestSuite with DataFrameComparer with ColumnCompar
         assert(math.abs(gammaMean - 4.0) < 0.5)
         assert(math.abs(gammaStddev - math.sqrt(8.0)) < 0.5)
       }
+
+      "has correct mean and standard deviation from shape/scale column" - {
+        val sourceDF = spark
+          .range(100000)
+          .withColumn("shape", lit(2.0))
+          .withColumn("scale", lit(2.0))
+          .select(randGamma(col("shape"), col("shape")))
+        val stats = sourceDF
+          .agg(
+            mean("gamma_random").as("mean"),
+            stddev("gamma_random").as("stddev")
+          )
+          .collect()(0)
+
+        val gammaMean   = stats.getAs[Double]("mean")
+        val gammaStddev = stats.getAs[Double]("stddev")
+
+        // Gamma distribution with shape=2.0 and scale=2.0 has mean=4.0 and stddev=sqrt(8.0)
+        assert(gammaMean > 0)
+        assert(math.abs(gammaMean - 4.0) < 0.5)
+        assert(math.abs(gammaStddev - math.sqrt(8.0)) < 0.5)
+      }
     }
 
     'rand_laplace - {