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java.lang.Object org.terrier.utility.StaTools
public class StaTools
This class implements a series of basic statistical functions.
Constructor Summary | |
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StaTools()
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Method Summary | |
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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 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 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 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 double |
variance(double[] data)
The variance of an array of double values. |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public StaTools()
Method Detail |
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public static double stirlingPower(double n, double m)
n
- The parameter of the Stirling formula.m
- The parameter of the Stirling formula.
public static double stdErrorOfTheMean(double[] data)
data
- The sampled data.
public static final int max(int[] a)
a
- the array
public static final double max(double[] a)
a
- the array
public static final double max(double[] a, int offset, int length)
a
- the arrayoffset
- the offset in the array to start examining fromlength
- how many items of the array to consider
public static final double min(double[] a)
a
- the array
public static final int min(int[] a)
a
- the array
public static int sum(int[] data)
data
- The integers.
public static double sum(double[] data)
data
- The integers.
public static double mean(double[] data)
data
- The double values.
public static float mean(float[] data)
data
-
public static double mean(double[] data, int start, int length, boolean ascending)
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?
public static double mean(int[] data)
data
- The array of integers.
public static double meanNonZero(double[] data)
data
- The array of integers.
public static double median(double[] data)
data
- The array of double values.
public static double standardDeviation(double[] data)
data
- The array of double values.
public static double variance(double[] data)
data
- The array of double values.
public static double harmonicMean(double[] data)
public static double geometricMean(double[] data)
public static double quadraticMean(double[] data)
public static double generalisedMean(double[] data, double p)
public static double[] standardNormalisation(double[] data)
data
-
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