tools

Type Members

1. case class CorrelationTestResult(covariance: Double, pearsonCoefficient: Double, spearmanCoefficient: Double, kendallsTauCoefficient: Double) extends Product with Serializable

   

2. case class DistributionTestPayload(testName: String, distribution: RealDistribution) extends Product with Serializable

   

3. case class DistributionTestResult(bestDistributionFit: String, bestDistributionPValue: Double, bestDistributionDStatistic: Double, allTests: Array[DistributionValidationData]) extends Product with Serializable

   

4. case class DistributionValidationData(test: String, pValue: Double, dStatistic: Double) extends Product with Serializable

   

5. case class KSTestResult(ksTestPvalue: Double, ksTestDStatistic: Double, ksTestEquivalency: Char) extends Product with Serializable

   

6. class OneDimStats extends AnyRef

   

   Package for testing a one-dimensional data set with standard data explanation metrics

   Package for testing a one-dimensional data set with standard data explanation metrics

   Attributes tested: Mean Geometric Mean Variance Semi Variance Standard Deviation Skew Kurtosis

   The return type also provides String classifications based on thresholds for Skew and Kurtosis to classify the distribution.

   Since

   0.7.0

   Note

   Kurtosis types: Mesokurtic - kurtosis around zero Leptokurtic - positive excess kurtosis (long heavy tails) Platykurtic - negative excess kurtosis (short thin tails) Skewness types: Symmetrical -> normal Asymmetricral Positive skewness -> right tailed Asymmetrical Negative skewness -> left tailed

7. case class OneDimStatsData(mean: Double, geomMean: Double, variance: Double, semiVariance: Double, stddev: Double, skew: Double, kurtosis: Double, kurtosisType: String, skewType: String, summaryStats: SummaryStats, distributionData: DistributionTestResult) extends Product with Serializable

   

8. case class PCACEigenResult(column: String, PCA1EigenVector: Double, PCA2EigenVector: Double) extends Product with Serializable

   

9. class PCAReducer extends SparkSessionWrapper

   

   API wrapper for conducting a 2-component PCA for visualizing a data set's feature relationships in a way that can be readily visualized.

   API wrapper for conducting a 2-component PCA for visualizing a data set's feature relationships in a way that can be readily visualized. Provides DataFrame export types for both the raw data with PC1 and PC2 values, as well as the eigen vector values.

10. case class PCAReducerResult(data: DataFrame, explainedVariances: Array[Double], pcMatrix: Array[PCACEigenResult], pcEigenDataFrame: DataFrame) extends Product with Serializable

    

11. case class PairedSeq(left: SummaryStatistics, right: SummaryStatistics) extends Product with Serializable

    

12. case class PairedTestResult(correlationTestData: CorrelationTestResult, tTestData: TTestData, kolmogorovSmirnovData: KSTestResult) extends Product with Serializable

    

13. class PairedTesting extends AnyRef

    

14. case class PolynomialRegressorResult(order: Int, function: PolynomialFunction, residualSumSquares: Double, sumSquareError: Double, totalSumSquares: Double, mse: Double, rmse: Double, r2: Double) extends Product with Serializable

    

15. case class RegressionBarData(xBar: Double, yBar: Double, xyBar: Double) extends Product with Serializable

    

16. case class RegressionCoefficients(slope: Double, intercept: Double, t1: Double, t2: Double, t3: Double) extends Product with Serializable

    

17. case class RegressionInternal(sumX: Double, sumY: Double, sumSqX: Double, sumSqY: Double, sumProduct: Double) extends Product with Serializable

    

18. case class RegressionResidualData(ssr: Double, rss: Double) extends Product with Serializable

    

19. trait ShapiroBase extends AnyRef

    

20. case class ShapiroInternalData(w: Double, z: Double, probability: Double, normalcyTest: Boolean, normalcy: String) extends Product with Serializable

    

21. case class ShapiroScoreData(w: Double, z: Double, probability: Double) extends Product with Serializable

    

22. case class SimpleRegressorResult(slope: Double, slopeStdErr: Double, slopeConfidenceInterval: Double, intercept: Double, interceptStdErr: Double, rSquared: Double, significance: Double, mse: Double, rmse: Double, sumSquares: Double, totalSumSquares: Double, sumSquareError: Double, pairLength: Long, pearsonR: Double, crossProductSum: Double) extends Product with Serializable

    

23. case class SummaryStats(count: Long, min: Double, max: Double, sum: Double, mean: Double, geometricMean: Double, variance: Double, popVariance: Double, secondMoment: Double, sumOfSquares: Double, stdDeviation: Double, sumOfLogs: Double) extends Product with Serializable

    

24. case class TTestData(alpha: Double, tStat: Double, tTestSignificance: Boolean, tTestPValue: Double, equivalencyJudgement: Char) extends Product with Serializable