
Constructors  public Outliers()  
public Outliers(double[] data)  
public Outliers(float[] data)  
public Outliers(long[] data)  
public Outliers(int[] data)  
public Outliers(BigDecimal[] data)  
public Outliers(BigInteger[] data)  
Read data in from a text file  public void readDataFromTextFile()  
Significance  Reset the significance level  public void resetSignificance(double significance) 
Get the significance level  public double getSignificance()  
Output text file  Reset the file name  public void resetTextFileName(String filename) 
Supress print to text file  public void suppressPrint()  
Restore print to text file  public void restorePrint()  
Display Probability Plots  Suppress display  public void suppressDisplay() 
Restore display  public void restoreDisplay()  
Grubbs’ Test  Instant methods  public ArrayList<Object> outlierGrubbs() 
public ArrayList<Object> lowerOutlierGrubbs()  
public ArrayList<Object> upperOutlierGrubbs()  
public double getGrubbsOneTailedCriticalT()  
public double getGrubbsTwoTailedCriticalT()  
Static methods  public static ArrayList<Object> outlierGrubbs(double[] data)  
public static ArrayList<Object> lowerOutlierGrubbs(double[] data)  
public static ArrayList<Object> upperOutlierGrubbs(double[] data)  
public static double getGrubbsOneTailedCriticalT(double significance, int nObservations)  
public static double getGrubbsTwoTailedCriticalT(double significance, int nObservations)  
TietjenMoore Test  Instant methods  public ArrayList<Object> outliersTietjenMoore(int nOutliers) 
public ArrayList<Object> lowerOutliersTietjenMoore(int nOutliers)  
public ArrayList<Object> upperOutliersTietjenMoore(int nOutliers)  
public double getTietjenMooreCriticalL(int nOutliers)  
public double getTietjenMooreLowerCriticalL(int nOutliers)  
public double getTietjenMooreUpperCriticalL(int nOutliers)  
Number of simulations  public void resetNumberTietjenMooreSimulations(int nSimulations)  
public int getNumberTietjenMooreSimulations()  
Static methods  public static ArrayList<Object> outliersTietjenMoore(double[] data, int nOutliers)  
public static ArrayList<Object> lowerOutliersTietjenMoore(double[] data, int nOutliers)  
public static ArrayList<Object> upperOutliersTietjenMoore(double[] data, int nOutliers)  
public static double getTietjenMooreCriticalL(int nOutliers, int nObservations, int nSimulations, double significance)  
public static double getTietjenMooreCriticalL(int nOutliers, int nObservations, double significance)  
public static double getTietjenMooreLowerCriticalL(int nOutliers, int nObservations, int nSimulations, double significance)  
public static double getTietjenMooreLowerCriticalL(int nOutliers, int nObservations, double significance)  
public static double getTietjenMooreUpperCriticalL(int nOutliers, int nObservations, int nSimulations, double significance)  
public static double getTietjenMooreUpperCriticalL(int nOutliers, int nObservations, double significance)  
Generalised ESD (Extreme Studentisied Deviate) Test  Instant methods  public ArrayList<Object> outliersESD(int nOutliers) 
Static methods  public static ArrayList<Object> outliersESD(double[] data, int nOutliers)  
public static double[] getESDlambdas(intrPoints, int nPoints, double significance)  
Dixon’s Q Test  Instant methods  public ArrayList<Object> outlierDixon(int a, int b); 
public ArrayList<Object> outlierDixon();  
public ArrayList<Object> lowerOutlierDixon(int a, int b);  
public ArrayList<Object> lowerOutlierDixon();  
public ArrayList<Object> upperOutlierDixon(int a, int b);  
public ArrayList<Object> upperOutlierDixon();  
Number of simulations  public void resetNumberDixonSimulations(int nSimulations)  
public int getNumberDixonSimulations()  
Static methods  public static ArrayList<Object> outlierDixon(double[] data, int a, int b)  
public static ArrayList<Object> outlierDixon(double[] data)  
public static ArrayList<Object> lowerOutlierDixon(double[] data, int a, int b)  
public static ArrayList<Object> lowerOutlierDixon(double[] data)  
public static ArrayList<Object> upperOutlierDixon(double[] data, int a, int b)  
public static ArrayList<Object> upperOutlierDixon(double[] data)  
public static double getDixonOneTailedCriticalQ(int a, int b, int nPoints, int nSimulations, double significance)  
public static double getDixonOneTailedCriticalQ(int a, int b, int nPoints, double significance)  
public static double getDixonOneTailedCriticalQ(int nPoints, int nSimulations, double significance)  
public static double getDixonOneTailedCriticalQ(int nPoints, double significance)  
public static double getDixonTwoTailedCriticalQ(int a, int b, int nPoints, int nSimulations, double significance)  
public static double getDixonTwoTailedCriticalQ(int a, int b, int nPoints, double significance)  
public static double getDixonTwoTailedCriticalQ(int nPoints, int nSimulations, double significance)  
public static double getDixonTwoTailedCriticalQ(int nPoints, double significance)  
public int[] ignoredIndicesLowerTest(int a, int b, int nPoints)  
public int[] ignoredIndicesUpperTest(int a, int b, int nPoints)  
Data  Get entered data as doubles  public double[] getOriginalData() 
public double[] getOrderedOriginalData()  
public double[] getDataOrderStatisticMedians()  
Get data stripped of outliers  public double[] getStrippedData()  
public double[] getOrderedStrippedData()  
public double[] getStrippedDataOrderStatisticMedians() 
element 0  (boolean)  true if an outlier identified, false if not 
element 1  (double)  the value of the outlier if an outlier identified, NaN if not 
element 2  (int)  the index of the outlier if an outlier identified, 1 if not 
element 3  (double[])  the data array with the outlier removed, the original data array if no outlier identified 
element 4  (double)  Grubbs’ G value 
element 5  (double)  Grubbs’ T_{n} value 
element 6  (double)  significance level used 
element 7  (int)  number of data points 
element 8  (double)  gradient of a Gaussian probability plot of the entered data 
element 9  (double)  intercept of a Gaussian probability plot of the entered data 
element 10  (double)  correlation coefficient, r, of a Gaussian probability plot of the entered data 
element 11  (double)  critical value for the correlation coefficient, r, of a Gaussian probability plot of the entered data at the significance level returned as element 6 
element 12  (double)  gradient of a Gaussian probability plot of the data with the outlier removed if outlier found, NaN otherwise 
element 13  (double)  intercept of a Gaussian probability plot of the data with the outlier removed if outlier found, NaN otherwise 
element 14  (double)  correlation coefficient, r, of a Gaussian probability plot of the data with the outlier removed if outlier found, NaN otherwise 
element 15  (double)  critical value for the correlation coefficient, r, of a Gaussian probability plot of the data with the outlier removed at the significance level returned as element 6 if outlier found, NaN otherwise 
element 16  (double)  ShapiroWilk W value for the entered data 
element 17  (double)  Critical value of the ShapiroWilk W value for the entered data at at the significance level returned as element 6 
element 18  (double)  ShapiroWilk p value for the entered data 
element 19  (double)  ShapiroWilk W value for the data with the outlier removed if outlier found, NaN otherwise 
element 20  (double)  Critical value of the ShapiroWilk W value for the data with the outlier removed at at the significance level returned as element 6 if outlier found, NaN otherwise 
element 21  (double)  ShapiroWilk p value for the data with the outlier removed if outlier found, NaN otherwise 
element 0  (boolean)  true if outliers identified, false if not 
element 1  (double[])  the value of the data points chosen as potential outliers [outliers if element 0 is true] 
element 2  (int[])  the indices of the potential/identified outliers. 
element 3  (double[])  the data array with the outliers removed, the original data array if no outliers identified 
element 4  (double)  data sample L_{k} value 
element 5  (double)  simulation L_{crit} value 
element 6  (double)  significance level used 
element 7  (double)  significance level at which L_{k} = L_{crit} 
element 8  (int)  number of data points 
element 9  (int)  number of outliers/possible outliers 
element 10  (double)  gradient of a Gaussian probability plot of the entered data 
element 11  (double)  intercept of a Gaussian probability plot of the entered data 
element 12  (double)  correlation coefficient, r, of a Gaussian probability plot of the entered data/td> 
element 13  (double)  critical value for the correlation coefficient, r, of a Gaussian probability plot of the entered data at the significance level returned as element 6 
element 14  (double)  gradient of a Gaussian probability plot of the data with the outlier removed if outlier/s found, NaN otherwise 
element 15  (double)  intercept of a Gaussian probability plot of the data with the outlier removed if outlier/s found, NaN otherwise 
element 16  (double)  correlation coefficient, r, of a Gaussian probability plot of the data with the outlier removed if outlier/s found, NaN otherwise 
element 17  (double)  critical value for the correlation coefficient, r, of a Gaussian probability plot of the data with the outlier removed at the significance level returned as element 6 if outlier/s found, NaN otherwise 
element 18  (double)  ShapiroWilk W value for the entered data 
element 19  (double)  Critical value of the ShapiroWilk W value for the entered data at at the significance level returned as element 6 
element 20  (double)  ShapiroWilk p value for the entered data 
element 21  (double)  ShapiroWilk W value for the data with the outlier removed if outlier found, NaN otherwise 
element 22  (double)  Critical value of the ShapiroWilk W value for the data with the outlier removed at at the significance level returned as element 6 if outlier found, NaN otherwise 
element 23  (double)  ShapiroWilk p value for the data with the outlier removed if outlier found, NaN otherwise 
element 0  (boolean)  true if outliers identified, false if not 
element 1  (double[])  the values of the data points indicated as outliers; null if no outliers indicated 
element 2  (int[])  the indices of the identified outliers; null if no outliers indicated 
element 3  (double[])  the data array with the outliers removed, the original data array if no outliers identified 
element 4  (double)  Test Statistics R_{i} value 
element 5  (double)  Critical Values λ_{i} 
element 6  (double)  true or false values for R_{i} > λ_{i} 
element 7  (double)  data values for the maximum ESDs 
element 8  (double)  significance level used 
element 9  (int)  number of data points 
element 10  (int)  number of points tested as possible outliers 
element 11  (double)  gradient of a Gaussian probability plot of the entered data 
element 12  (double)  intercept of a Gaussian probability plot of the entered data 
element 13  (double)  correlation coefficient, r, of a Gaussian probability plot of the entered data 
element 14  (double)  critical value for the correlation coefficient, r, of a Gaussian probability plot of the entered data at the significance level returned as element 6 
element 15  (double)  gradient of a Gaussian probability plot of the data with the outlier removed if outlier/s found, NaN otherwise 
element 16  (double)  intercept of a Gaussian probability plot of the data with the outlier removed if outlier/s found, NaN otherwise 
element 17  (double)  correlation coefficient, r, of a Gaussian probability plot of the data with the outlier/s removed if outlier found, NaN otherwise 
element 18  (double)  critical value for the correlation coefficient, r, of a Gaussian probability plot of the data with the outlier removed at the significance level returned as element 6 if outlier found, NaN otherwise 
element 19  (double)  ShapiroWilk W value for the entered data 
element 20  (double)  Critical value of the ShapiroWilk W value for the entered data at at the significance level returned as element 6 
element 21  (double)  ShapiroWilk p value for the entered data 
element 22  (double)  ShapiroWilk W value for the data with the outlier removed if outlier found, NaN otherwise 
element 23  (double)  Critical value of the ShapiroWilk W value for the data with the outlier removed at at the significance level returned as element 6 if outlier found, NaN otherwise 
element 24  (double)  ShapiroWilk p value for the data with the outlier removed if outlier found, NaN otherwise 
element 0  (boolean)  true if outliers identified, false if not 
element 1  (double)  the value of outlier; NaN if no outlier found 
element 2  (int)  the index of the outlier point; 1 if no outlier found. 
element 3  (double[])  the data array with the outliers removed, the original data array if no outliers identified 
element 4  (double)  data sample r_{ab} value 
element 5  (double)  simulation Q_{crit} value 
element 6  (double)  significance level used 
element 7  (int)  number of data points 
element 8  (int)  value of a in r_{ab} 
element 9  (int)  value of b in r_{ab} 
element 10  (int)  number of points ignored 
element 11  (double[])  values of ignored points; null if no points ignored 
element 12  (double)  gradient of a Gaussian probability plot of the entered data 
element 13  (double)  intercept of a Gaussian probability plot of the entered data 
element 14  (double)  correlation coefficient, r, of a Gaussian probability plot of the entered data 
element 15  (double)  critical value for the correlation coefficient, r, of a Gaussian probability plot of the entered data at the significance level returned as element 6 
element 16  (double)  gradient of a Gaussian probability plot of the data with the outlier removed if outlier found, NaN otherwise 
element 17  (double)  intercept of a Gaussian probability plot of the data with the outlier removed if outlier found, NaN otherwise 
element 18  (double)  correlation coefficient, r, of a Gaussian probability plot of the data with the outlier removed if outlier found, NaN otherwise 
element 19  (double)  critical value for the correlation coefficient, r, of a Gaussian probability plot of the data with the outlier removed at the significance level returned as element 6 if outlier found, NaN otherwise 
element 20  (double)  ShapiroWilk W value for the entered data 
element 21  (double)  Critical value of the ShapiroWilk W value for the entered data at at the significance level returned as element 6 
element 22  (double)  ShapiroWilk p value for the entered data 
element 23  (double)  ShapiroWilk W value for the data with the outlier removed if outlier found, NaN otherwise 
element 24  (double)  Critical value of the ShapiroWilk W value for the data with the outlier removed at at the significance level returned as element 6 if outlier found, NaN otherwise 
element 25  (double)  ShapiroWilk p value for the data with the outlier removed if outlier found, NaN otherwise 