XYStats (Starjava TTOOLS API)

java.lang.Object

uk.ac.starlink.ttools.plot.XYStats

public class XYStats extends Object

Calculates X-Y correlation statistics.

Since:: 15 Jul 2004
Author:: Mark Taylor (Starlink)

Constructor Summary

Constructors

Constructor

Description

XYStats(boolean xLog, boolean yLog)

Constructs a new correlation statistics calculator.
Method Summary

Modifier and Type

Method

Description

void

addPoint(double x, double y)

Submits a data point for calculations.

double

getCorrelation()

Returns the product moment correlation coefficient.

double[]

getLinearCoefficients()

Returns the polynomial coefficients of a linear regression line for the submitted data.

double[]

linearRegressionLine()

Calculates the linear regression line for the submitted points.

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

Constructor Details
- XYStats
  
  public XYStats(boolean xLog, boolean yLog)
  
  Constructs a new correlation statistics calculator.
  
  Parameters:
  
  xLog - whether the X coordinates are being plotted on a logarithmic scale
  
  yLog - whether the Y coordinates are being plotted on a logarithmic scale
Method Details
- addPoint
  
  public void addPoint(double x, double y)
  
  Submits a data point for calculations.
  
  Parameters:
  
  x - X coordinate
  
  y - Y coordinate
- getLinearCoefficients
  
  public double[] getLinearCoefficients()
  
  Returns the polynomial coefficients of a linear regression line for the submitted data.
  
  Returns:
  
  2-element array: (intercept, gradient)
- getCorrelation
  
  public double getCorrelation()
  
  Returns the product moment correlation coefficient.
  
  Returns:
  
  correlation coefficient
- linearRegressionLine
  
  public double[] linearRegressionLine()
  
  Calculates the linear regression line for the submitted points. The endpoints of the line correspond to the lowest and highest X values submitted.
  
  Returns:
  
  4-element array giving the endpoints (low-X, low-Y, high-X, high-Y) of a linear regression line for these data