refactoring
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@ -5,7 +5,6 @@
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package space.kscience.kmath.series
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package space.kscience.kmath.series
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import space.kscience.kmath.distributions.NormalDistribution
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import space.kscience.kmath.operations.DoubleBufferOps.Companion.map
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import space.kscience.kmath.operations.DoubleBufferOps.Companion.map
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import space.kscience.kmath.operations.DoubleField.pow
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import space.kscience.kmath.operations.DoubleField.pow
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import space.kscience.kmath.operations.algebra
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import space.kscience.kmath.operations.algebra
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@ -18,6 +17,12 @@ public data class VarianceRatioTestResult(val varianceRatio: Double, val zScore:
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public fun varianceRatioTest(series: Series<Double>, shift: Int, homoscedastic: Boolean): VarianceRatioTestResult {
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public fun varianceRatioTest(series: Series<Double>, shift: Int, homoscedastic: Boolean): VarianceRatioTestResult {
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/**
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* Calculate the Z statistic and the p-value for the Lo and MacKinlay's Variance Ratio test (1987)
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* under Homoscedastic or Heteroscedstic assumptions
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* https://ssrn.com/abstract=346975
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* **/
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val sum = { x: Double, y: Double -> x + y }
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val sum = { x: Double, y: Double -> x + y }
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val mean = series.fold(0.0, sum) / series.size
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val mean = series.fold(0.0, sum) / series.size
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