diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/series/VarianceRatio.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/series/VarianceRatioTest.kt
similarity index 90%
rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/series/VarianceRatio.kt
rename to kmath-stat/src/commonMain/kotlin/space/kscience/kmath/series/VarianceRatioTest.kt
index 2dfcd6b00..77163f638 100644
--- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/series/VarianceRatio.kt
+++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/series/VarianceRatioTest.kt
@@ -5,7 +5,6 @@
 
 package space.kscience.kmath.series
 
-import space.kscience.kmath.distributions.NormalDistribution
 import space.kscience.kmath.operations.DoubleBufferOps.Companion.map
 import space.kscience.kmath.operations.DoubleField.pow
 import space.kscience.kmath.operations.algebra
@@ -18,6 +17,12 @@ public data class VarianceRatioTestResult(val varianceRatio: Double, val zScore:
 
 public fun varianceRatioTest(series: Series<Double>, shift: Int, homoscedastic: Boolean): VarianceRatioTestResult {
 
+    /**
+     * Calculate the Z statistic and the p-value for the Lo and MacKinlay's Variance Ratio test (1987)
+     * under Homoscedastic or Heteroscedstic assumptions
+     * 	https://ssrn.com/abstract=346975
+     * **/
+
     val sum = { x: Double, y: Double -> x + y }
 
     val mean = series.fold(0.0, sum) / series.size