Package org.terrier.utility

Class StaTools

java.lang.Object

org.terrier.utility.StaTools

public class StaTools
extends java.lang.Object

This class implements a series of basic statistical functions.

Constructor Summary

Constructors

Constructor	Description
StaTools()

Method Summary

Modifier and Type	Method	Description
static double	generalisedMean(double[] data, double p)	Computes the generalized mean, which is a general version of mean and quadratic mean, generalized by parameter p.
static double	geometricMean(double[] data)	Computes the geometric mean.
static double	harmonicMean(double[] data)	Computes the harmonic mean.
static double	max(double[] a)	Return the max of the specified array
static double	max(double[] a, int offset, int length)	Return the max of the specified array
static float	max(float[] a)	Return the max of the specified array
static int	max(int[] a)	Return the max of the specified array
static double	mean(double[] data)	The mean of an array of double values.
static double	mean(double[] data, int start, int length, boolean ascending)	The mean of a sub-array of an array of double values.
static float	mean(float[] data)	find mean of float[]
static double	mean(int[] data)	The mean of an array of integers.
static double	meanNonZero(double[] data)	The mean of an array of doubles, only counting non-zero values.
static double	median(double[] data)	The median of an array of double values.
static double	min(double[] a)	Return the min of the specified array
static float	min(float[] a)	Return the min of the specified array
static int	min(int[] a)	Return the min of the specified array
static double	quadraticMean(double[] data)	Computes the quadratic mean, also known as the root mean square.
static double	standardDeviation(double[] data)	The standard deviation of an array of double values.
static double[]	standardNormalisation(double[] data)	Normalises the data in the specified array to be in range [0,1], with 0 as the minimum, and 1 as the maximum.
static float[]	standardNormalisation(float[] data)	Normalises the data in the specified array to be in range [0,1], with 0 as the minimum, and 1 as the maximum.
static double	stdErrorOfTheMean(double[] data)	This method returns the standard error of the mean for an array of data.
static double	stirlingPower(double n, double m)	This method provides the contract for implementing the Stirling formula for the power series.
static double	sum(double[] data)	The sum of an array of double.
static int	sum(int[] data)	The sum of an array of integers.
static int	sum(int[] data, int length)	The sum of an array of integers.
static double	variance(double[] data)	The variance of an array of double values.

Methods inherited from class java.lang.Object

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

Constructor Detail

StaTools

public StaTools()

Method Detail

stirlingPower

public static double stirlingPower(double n,
                                   double m)

This method provides the contract for implementing the Stirling formula for the power series.

Parameters:

n - The parameter of the Stirling formula.

m - The parameter of the Stirling formula.

Returns:

the approximation of the power series

stdErrorOfTheMean

public static double stdErrorOfTheMean(double[] data)

This method returns the standard error of the mean for an array of data.

Parameters:

data - The sampled data.

Returns:

The standard error of the mean.

max

public static final int max(int[] a)

Return the max of the specified array

Parameters:

a - the array

Returns:

the maximum value in the arrays

max

public static final double max(double[] a)

Return the max of the specified array

Parameters:

a - the array

Returns:

the maximum value in the arrays

max

public static final double max(double[] a,
                               int offset,
                               int length)

Return the max of the specified array

Parameters:

a - the array

offset - the offset in the array to start examining from

length - how many items of the array to consider

Returns:

the maximum value in the arrays

min

public static final double min(double[] a)

Return the min of the specified array

Parameters:

a - the array

Returns:

the minimum value in the arrays

min

public static final int min(int[] a)

Return the min of the specified array

Parameters:

a - the array

Returns:

the minimum value in the arrays

sum

public static int sum(int[] data)

The sum of an array of integers.

Parameters:

data - The integers.

Returns:

The sum.

sum

public static int sum(int[] data,
                      int length)

The sum of an array of integers.

Parameters:

data - The integers.

Returns:

The sum.

sum

public static double sum(double[] data)

The sum of an array of double.

Parameters:

data - The integers.

Returns:

The sum.

mean

public static double mean(double[] data)

The mean of an array of double values.

Parameters:

data - The double values.

Returns:

The mean.

mean

public static float mean(float[] data)

find mean of float[]

Parameters:

data -

Returns:

mean

mean

public static double mean(double[] data,
                          int start,
                          int length,
                          boolean ascending)

The mean of a sub-array of an array of double values.

Parameters:

data - The array of double values.

start - The starting index of the sub-array.

length - The length of the sub-array.

ascending - Is the starting index the left (true) or right (false) end of the sub-array?

Returns:

The mean of the sub-array.

mean

public static double mean(int[] data)

The mean of an array of integers.

Parameters:

data - The array of integers.

Returns:

The mean.

meanNonZero

public static double meanNonZero(double[] data)

The mean of an array of doubles, only counting non-zero values.

Parameters:

data - The array of integers.

Returns:

The mean.

median

public static double median(double[] data)

The median of an array of double values.

Parameters:

data - The array of double values.

Returns:

The median.

standardDeviation

public static double standardDeviation(double[] data)

The standard deviation of an array of double values.

Parameters:

data - The array of double values.

Returns:

The standrad deviation.

variance

public static double variance(double[] data)

The variance of an array of double values.

Parameters:

data - The array of double values.

Returns:

The variance.

harmonicMean

public static double harmonicMean(double[] data)

Computes the harmonic mean. This assumes that all values are > 0. See http://en.wikipedia.org/wiki/Harmonic_mean.

geometricMean

public static double geometricMean(double[] data)

Computes the geometric mean. This assumes that all values are > 0. See http://en.wikipedia.org/wiki/Geometric_mean.

quadraticMean

public static double quadraticMean(double[] data)

Computes the quadratic mean, also known as the root mean square. See http://en.wikipedia.org/wiki/Quadratic_mean.

generalisedMean

public static double generalisedMean(double[] data,
                                     double p)

Computes the generalized mean, which is a general version of mean and quadratic mean, generalized by parameter p. See http://en.wikipedia.org/wiki/Generalized_mean.

standardNormalisation

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

Normalises the data in the specified array to be in range [0,1], with 0 as the minimum, and 1 as the maximum. RETURNS THE SAME ARRAY OBJECT - i.e. changes are made in place.

Parameters:

data -

standardNormalisation

public static float[] standardNormalisation(float[] data)

Normalises the data in the specified array to be in range [0,1], with 0 as the minimum, and 1 as the maximum. RETURNS THE SAME ARRAY OBJECT - i.e. changes are made in place.

Parameters:

data -

min

public static final float min(float[] a)

Return the min of the specified array

Parameters:

a - the array

Returns:

the minimum value in the arrays

max

public static final float max(float[] a)

Return the max of the specified array

Parameters:

a - the array

Returns:

the maximum value in the arrays