Statistics (Jzy3d API 1.0.0-SNAPSHOT API)

java.lang.Object
- org.jzy3d.maths.Statistics

```
public class Statistics
extends Object
```

Constructor Summary

Constructors
Constructor and Description

Statistics()

Constructors
Constructor and Description
`Statistics()`

Method Summary

All Methods Static Methods Concrete Methods
Modifier and Type	Method and Description
`static double`	`mad(double[] values)` Computes the mad statistic, that is the median of all distances to the median of input values.
`static double`	`max(double[] values)` Computes the maximum value of an array of doubles.
`static float`	`max(float[] values)`
`static float`	`max(float[][] values)`
`static int`	`max(int[][] values)`
`static float`	`max(List<Float> values)`
`static int`	`maxId(int[] values)`
`static double`	`mean(double[] values)` Computes the mean value of an array of doubles.
`static float`	`mean(float[] values)`
`static double`	`median(double[] values, boolean interpolated)` Computes the median value of an array of doubles.
`static double`	`min(double[] values)` Computes the minimum value of an array of doubles.
`static float`	`min(float[] values)`
`static float`	`min(float[][] values)`
`static int`	`min(int[][] values)`
`static float`	`min(List<Float> values)`
`static int`	`minId(double[] values)` Returns the id where the minimal value stands.
`static int`	`minId(float[] values)`
`static int`	`minId(int[] values)`
`static double[]`	`quantile(double[] values, double[] levels)` A convenient shortcut for: quantile(values, levels, true);
`static double[]`	`quantile(double[] values, double[] levels, boolean interpolated)` Computes the quantiles of an array of doubles.
`static double`	`std(double[] values)` Computes the standard deviation of an array of doubles.
`static double`	`variance(double[] values)` Compute the variance of an array of doubles.

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

- Constructor Detail
  - Statistics
```
public Statistics()
```
- Method Detail
  - mean
```
public static double mean(double[] values)
```
    Computes the mean value of an array of doubles. NaN values are ignored during the computation.
    
    Parameters:
    
    values -
    
    Returns:
    
    the mean value
  - mean
```
public static float mean(float[] values)
```
  - min
```
public static float min(List<Float> values)
```
  - min
```
public static double min(double[] values)
```
    Computes the minimum value of an array of doubles. NaN values are ignored during the computation.
    
    Parameters:
    
    values -
    
    Returns:
    
    the minimum value
  - min
```
public static float min(float[] values)
```
  - min
```
public static float min(float[][] values)
```
  - min
```
public static int min(int[][] values)
```
  - minId
```
public static int minId(double[] values)
```
    Returns the id where the minimal value stands.
  - minId
```
public static int minId(float[] values)
```
  - minId
```
public static int minId(int[] values)
```
  - max
```
public static float max(List<Float> values)
```
  - max
```
public static double max(double[] values)
```
    Computes the maximum value of an array of doubles. NaN values are ignored during the computation.
    
    Parameters:
    
    values -
    
    Returns:
    
    the maximum value
  - max
```
public static float max(float[] values)
```
  - max
```
public static float max(float[][] values)
```
  - max
```
public static int max(int[][] values)
```
  - maxId
```
public static int maxId(int[] values)
```
  - mad
```
public static double mad(double[] values)
```
    Computes the mad statistic, that is the median of all distances to the median of input values. If the input array is empty, the output value is Double.NaN
    
    Parameters:
    
    values -
    
    Returns:
  - std
```
public static double std(double[] values)
```
    Computes the standard deviation of an array of doubles. NaN values are ignored during the computation. If the input array is empty, the output value is Double.NaN
    
    Parameters:
    
    values -
    
    Returns:
    
    the standard deviation
  - variance
```
public static double variance(double[] values)
```
    Compute the variance of an array of doubles. variance normalizes the output by N-1 if N>1, where N is the sample size. This is an unbiased estimator of the variance of the population For N=1, the output is 0.
    
    Parameters:
    
    values -
    
    Returns:
  - quantile
```
public static double[] quantile(double[] values,
                                double[] levels,
                                boolean interpolated)
```
    Computes the quantiles of an array of doubles. This method assumes the array has at least one element. NaN values are ignored during the computation.
    
    Parameters:
    
    values -
    
    levels - a list of levels that must belong to [0;100]
    
    interpolated - computes an interpolation of quantile when required quantile is not an exact vector id.
    
    Returns:
    
    the quantiles
    
    Throws:
    
    an - IllegalArgumentException if a level is out of the [0;100] bounds.
  - quantile
```
public static double[] quantile(double[] values,
                                double[] levels)
```
    A convenient shortcut for: quantile(values, levels, true);
    
    Parameters:
    
    values -
    
    levels -
    
    Returns:
  - median
```
public static double median(double[] values,
                            boolean interpolated)
```
    Computes the median value of an array of doubles.
    
    Parameters:
    
    values -
    
    interpolated -
    
    Returns:
    
    the mean value

Class Statistics

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

Statistics

Method Detail

mean

mean

min

min

min

min

min

minId

minId

minId

max

max

max

max

max

maxId

mad

std

variance

quantile

quantile

median