org.terrier.utility

## Class StaTools

• ```public class StaTools
extends Object```
This class implements a series of basic statistical functions.
• ### Constructor Summary

Constructors
Constructor and Description
`StaTools()`
• ### Method Summary

Methods
Modifier and Type Method and 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:
• #### 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.

`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