Catalano.Statistics

Class Tools

java.lang.Object

Catalano.Statistics.Tools

public class Tools
extends java.lang.Object

Common tools used in statistics.

Method Summary

Modifier and Type	Method and Description
static double	AlphaTrimmedMean(double[] values, float alpha) Alpha Trimmed Mean
static double	AlphaTrimmedMean(double[] values, int n) Alpha Trimmed Mean
static double	AlphaTrimmedMean(int[] values, float alpha) Alpha Trimmed Mean
static double	AlphaTrimmedMean(int[] values, int n) Alpha Trimmed Mean
static double	CoefficientOfVariation(double[] x) Coefficient of variation.
static double	ContraHarmonicMean(double[] x, int order) Contra Harmonic mean.
static double[][]	Correlation(double[][] data) Create a pearson correlation matrix.
static double[][]	Covariance(double[][] matrix) Matrix of covariance.
static double[][]	Covariance(double[][] matrix, double[] means) Matrix of covariance.
static double	Covariance(double[] x, double[] y) Covariance between vector x and y.
static double	Covariance(double[] x, double[] y, double meanX, double meanY) Covariance between vector x and y.
static double	Fisher(double n) Fisher.
static double	GeometricMean(double[] x) Geometric mean.
static double	HarmonicMean(double[] x) Harmonic mean.
static double	Inclination(double[] x, double[] y) Inclination.
static double	Interception(double[] x, double[] y) Interception.
static double	InverseFisher(double n) Inverse fisher.
static double	Max(double[] x) Maximum element.
static double	Mean(double[] x) Mean.
static double[]	Mean(double[][] data) Mean of the matrix for each column.
static double	Min(double[] x) Minimum element.
static double	Mode(double[] values) Mode of the vector.
static int	Mode(int[] values) Mode of the vector.
static double	StandartDeviation(double[] x) Standart deviation.
static double[]	StandartDeviation(double[][] data) Standart deviation for each column.
static double[]	StandartDeviation(double[][] data, double[] means) Standart deviation for each column.
static double	StandartDeviation(double[] x, double mean) Standart deviation.
static double	Sum(double[] x) Sum.
static double	Variance(double[] x) Variance
static double	Variance(double[] x, double mean) Variance.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Detail

AlphaTrimmedMean

public static double AlphaTrimmedMean(double[] values,
                                      float alpha)

Alpha Trimmed Mean

Parameters:

values - Values.

alpha - Percentage [0..1]

Returns:

Alpha trimmed mean.

AlphaTrimmedMean

public static double AlphaTrimmedMean(double[] values,
                                      int n)

Alpha Trimmed Mean

Parameters:

values - Values.

n - Number of elements.

Returns:

Alpha trimmed mean.

AlphaTrimmedMean

public static double AlphaTrimmedMean(int[] values,
                                      float alpha)

Alpha Trimmed Mean

Parameters:

values - Values.

alpha - Percentage [0..1]

Returns:

Alpha trimmed mean.

AlphaTrimmedMean

public static double AlphaTrimmedMean(int[] values,
                                      int n)

Alpha Trimmed Mean

Parameters:

values - Values.

n - Number of elements.

Returns:

Alpha trimmed mean.

CoefficientOfVariation

public static double CoefficientOfVariation(double[] x)

Coefficient of variation.

Parameters:

x - Vector.

Returns:

Coefficient of variation.

Correlation

public static double[][] Correlation(double[][] data)

Create a pearson correlation matrix.

Parameters:

data - Data.

Returns:

Correlation matrix.

Covariance

public static double Covariance(double[] x,
                                double[] y)

Covariance between vector x and y.

Parameters:

x - Vector.

y - Vector.

Returns:

Covariance between x and y.

Covariance

public static double Covariance(double[] x,
                                double[] y,
                                double meanX,
                                double meanY)

Covariance between vector x and y.

Parameters:

x - Vector.

y - Vector.

meanX - X mean.

meanY - Y mean.

Returns:

Covariance between x and y.

Covariance

public static double[][] Covariance(double[][] matrix)

Matrix of covariance.

Parameters:

matrix - Matrix.

Returns:

Matrix of covariance.

Covariance

public static double[][] Covariance(double[][] matrix,
                                    double[] means)

Matrix of covariance.

Parameters:

matrix - Matrix.

means - Means.

Returns:

Matrix of covariance.

Fisher

public static double Fisher(double n)

Fisher.

Parameters:

n - Number.

Returns:

Fisher number.

Inclination

public static double Inclination(double[] x,
                                 double[] y)

Inclination.

Parameters:

x - Vector.

y - Vector.

Returns:

Inclination between the vector x and y.

InverseFisher

public static double InverseFisher(double n)

Inverse fisher.

Parameters:

n - Number.

Returns:

Inverse fisher of the number.

Interception

public static double Interception(double[] x,
                                  double[] y)

Interception.

Parameters:

x - Vector.

y - Vector.

Returns:

Interception between the vector x and y.

Max

public static double Max(double[] x)

Maximum element.

Parameters:

x - Vector.

Returns:

Maximum element of the vector,

Mean

public static double Mean(double[] x)

Mean.

Parameters:

x - Vector.

Returns:

Mean of the vector.

Mean

public static double[] Mean(double[][] data)

Mean of the matrix for each column.

Parameters:

data - Data.

Returns:

Mean of the each column.

Min

public static double Min(double[] x)

Minimum element.

Parameters:

x - Vector.

Returns:

Minimum element of the vector.

Mode

public static double Mode(double[] values)

Mode of the vector.

Parameters:

values - Values.

Returns:

Mode.

Mode

public static int Mode(int[] values)

Mode of the vector.

Parameters:

values - Values.

Returns:

Mode.

GeometricMean

public static double GeometricMean(double[] x)

Geometric mean.

Parameters:

x - Vector.

Returns:

Geometric mean.

HarmonicMean

public static double HarmonicMean(double[] x)

Harmonic mean.

Parameters:

x - Vector.

Returns:

Harmonic mean.

ContraHarmonicMean

public static double ContraHarmonicMean(double[] x,
                                        int order)

Contra Harmonic mean.

Parameters:

x - Vector.

order - Order.

Returns:

Contra Harmonic mean.

Sum

public static double Sum(double[] x)

Sum.

Parameters:

x - Vector.

Returns:

Sum of the all elements.

Variance

public static double Variance(double[] x)

Variance

Parameters:

x - Vector.

Returns:

Variance of the vector.

Variance

public static double Variance(double[] x,
                              double mean)

Variance.

Parameters:

x - Vector.

mean - Mean.

Returns:

Variance of the vector.

StandartDeviation

public static double StandartDeviation(double[] x)

Standart deviation.

Parameters:

x - Vector.

Returns:

Standart deviation of the vector.

StandartDeviation

public static double StandartDeviation(double[] x,
                                       double mean)

Standart deviation.

Parameters:

x - Vector.

mean - Mean.

Returns:

Standart deviation of the vector.

StandartDeviation

public static double[] StandartDeviation(double[][] data)

Standart deviation for each column.

Parameters:

data - Data.

Returns:

Standart deviation of the data.

StandartDeviation

public static double[] StandartDeviation(double[][] data,
                                         double[] means)

Standart deviation for each column.

Parameters:

data - Data.

means - Means of the columns.

Returns:

Standart deviation of the data.