SampleStats (Support and utility classes 1.6.0 API)

java.lang.Object
- org.jaitools.numeric.SampleStats

```
public class SampleStats
extends Object
```
A collection of static methods to calculate summary statistics for a sample of double-valued data. This class is used by both Jiffle and the KernelStats operator.

Since:

1.0

Version:

$Id$

Author:

Michael Bedward, Daniele Romagnoli, GeoSolutions S.A.S.

Constructor Summary

Constructors
Constructor and Description

SampleStats()

Constructors
Constructor and Description
`SampleStats()`

Method Summary

All Methods Static Methods Concrete Methods
Modifier and Type	Method and Description
`static double`	`max(Double[] values, boolean ignoreNaN)` Return the maximum of the given values.
`static double`	`mean(Double[] values, boolean ignoreNaN)` Return the mean of the given values.
`static double`	`median(Double[] values, boolean ignoreNaN)` Calculates the median of the given values.
`static double`	`min(Double[] values, boolean ignoreNaN)` Calculates the minimum of the given values.
`static double`	`mode(Double[] values, boolean ignoreNaN)` Calculates the empirical mode (highest frequency value) of the given values.
`static double`	`range(Double[] values, boolean ignoreNaN)` Calculates the range (max - min) of a set of values.
`static double`	`sdev(Double[] values, boolean ignoreNaN)` Calculates sample standard deviation.
`static double`	`sum(Double[] values, boolean ignoreNaN)` Calculates the sum of the values.
`static double`	`variance(Double[] values, boolean ignoreNaN)` Calculates sample variance using the running sample algorithm of Welford (1962) described by Knuth in The Art of Computer Programming (3rd ed) Vol.2 p.232

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - SampleStats
```
public SampleStats()
```
- Method Detail
  - max
```
public static double max(Double[] values,
                         boolean ignoreNaN)
```
    Return the maximum of the given values.
    
    Parameters:
    
    values - sample values
    
    ignoreNaN - specifies whether to ignore NaN values
    
    Returns:
    
    max value or Double.NaN if the sample is empty
  - mean
```
public static double mean(Double[] values,
                          boolean ignoreNaN)
```
    Return the mean of the given values.
    
    Parameters:
    
    values - sample values
    
    ignoreNaN - specifies whether to ignore NaN values
    
    Returns:
    
    mean value or Double.NaN if the sample is empty
  - min
```
public static double min(Double[] values,
                         boolean ignoreNaN)
```
    Calculates the minimum of the given values.
    
    Parameters:
    
    values - sample values
    
    ignoreNaN - specifies whether to ignore NaN values
    
    Returns:
    
    min value or Double.NaN if the sample is empty
  - median
```
public static double median(Double[] values,
                            boolean ignoreNaN)
```
    Calculates the median of the given values. For a sample with an odd number of elements the median is the mid-point value of the sorted sample. For an even number of elements it is the mean of the two values on either side of the mid-point.
    
    Parameters:
    
    values - sample values (need not be pre-sorted)
    
    ignoreNaN - specifies whether to ignore NaN values
    
    Returns:
    
    median value or Double.NaN if the sample is empty
  - mode
```
public static double mode(Double[] values,
                          boolean ignoreNaN)
```
    Calculates the empirical mode (highest frequency value) of the given values. Double.NaN values are ignored. If more than one data value occurs with maximum frequency the following tie-break rules are used:
    - for an odd number of tied values, return their median
    - for an even number of tied values, return the value below the mid-point of the sorted list of tied values
    This ensures that the calculated mode occurs in the sample data. Whether or not the mode is meaningful for the sample is up to the user !
    Parameters:
    
    values - sample values
    
    ignoreNaN - specifies whether to ignore NaN values
    
    Returns:
    
    calculated mode or Double.NaN if the sample is empty
  - range
```
public static double range(Double[] values,
                           boolean ignoreNaN)
```
    Calculates the range (max - min) of a set of values.
    
    Parameters:
    
    values - sample values
    
    ignoreNaN - specifies whether to ignore NaN values
    
    Returns:
    
    the range or Double.NaN if the set is empty
  - variance
```
public static double variance(Double[] values,
                              boolean ignoreNaN)
```
    Calculates sample variance using the running sample algorithm of Welford (1962) described by Knuth in The Art of Computer Programming (3rd ed) Vol.2 p.232
    
    Parameters:
    
    values - sample values
    
    ignoreNaN - specifies whether to ignore NaN values
    
    Returns:
    
    sample variance
  - sdev
```
public static double sdev(Double[] values,
                          boolean ignoreNaN)
```
    Calculates sample standard deviation. This is a convenience method that calls variance(java.lang.Double[], boolean) and returns the square-root of the result
    
    Parameters:
    
    values - sample values
    
    ignoreNaN - specifies whether to ignore NaN values
    
    Returns:
    
    sample standard deviation as a double
  - sum
```
public static double sum(Double[] values,
                         boolean ignoreNaN)
```
    Calculates the sum of the values.
    
    Parameters:
    
    values - sample values
    
    ignoreNaN - specifies whether to ignore NaN values
    
    Returns:
    
    sum of the values

Class SampleStats

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

SampleStats

Method Detail

max

mean

min

median

mode

range

variance

sdev

sum