org.jzy3d.maths
Class Statistics

java.lang.Object
  extended by org.jzy3d.maths.Statistics

public class Statistics
extends java.lang.Object


Constructor Summary
Statistics()
           
 
Method Summary
static double[] levels(int n)
          Produce a regular level list for easy quantiles
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 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 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 sum(double[] values)
           
static float sum(float[] values)
           
static int sum(int[] values)
           
static double variance(double[] values)
          Compute the variance of an array of doubles.
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

Statistics

public Statistics()
Method Detail

sum

public static double sum(double[] values)

sum

public static float sum(float[] values)

sum

public static int sum(int[] values)

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 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 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:

levels

public static double[] levels(int n)
Produce a regular level list for easy quantiles

Parameters:
n -
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