LinReg

java.lang.Object
- jhplot.stat.LinReg

public class LinReg
extends java.lang.Object

A linear regression analysis.

Constructor Summary

Constructors
Constructor and Description

LinReg(double[] aX, double[] aY)
Constructor for regression calculations

LinReg(P1D aXY)
constructor for regression calculations.

Constructors
Constructor and Description
`LinReg(double[] aX, double[] aY)` Constructor for regression calculations
`LinReg(P1D aXY)` constructor for regression calculations.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`addPoint(double xValue, double yValue)` Add a point to the data and redo the regression
`void`	`doc()` Show online documentation.
`P1D[]`	`getConfidence()` Get confidence intervals for means
`P1D[]`	`getConfidence(java.awt.Color color)` Get confidence intervals for means
`P1D`	`getConfidenceBand(java.awt.Color color, double transparency)` Calculate confidence band in form of P1D with errors.
`P1D`	`getConfidenceBand(int Npoints, java.awt.Color color, double transparency)` Calculate confidence band in form of P1D with errors.
`double`	`getCorrelation()` Get correlation coefficient
`int`	`getDataLength()` Get the size of the input data
`double[]`	`getDataX()` Get an array with X data
`double[]`	`getDataY()` Get an array with Y data
`double`	`getIntercept()` Get Intercept
`double`	`getInterceptError()` Get the standard error on intercept
`double`	`getMaxAbsoluteResidual()` Get max absolute residual
`double`	`getMaxX()` Get a maximum value for X
`double`	`getMaxY()` Get maximum value in Y
`double`	`getMinX()` Get a minimum value for X
`double`	`getMinY()` Get minimum value for Y
`double`	`getMSE()` Get MSE value
`double`	`getPearsonR()` Get pearson R
`P1D[]`	`getPrediction()` Get prediction lines
`P1D[]`	`getPrediction(java.awt.Color color)` Get prediction lines
`P1D`	`getPredictionBand()` Calculate the prediction band in form of P1D with errors.
`P1D`	`getPredictionBand(java.awt.Color color)` Calculate the prediction band in form of P1D with errors.
`P1D`	`getPredictionBand(java.awt.Color color, double transparency)` Calculate the prediction band in form of P1D with errors.
`P1D`	`getPredictionBand(int Npoints, java.awt.Color color, double transparency)` Calculate the prediction band in form of P1D with errors.
`P1D`	`getResiduals()` Get residuals
`F1D`	`getResult()` Get the linear regression result
`double`	`getSlope()` Get slope
`double`	`getSlopeError()` Get the standard error on slope
`double`	`getSSE()` Get SSE value
`double`	`getSSR()` Ger SSR value
`double`	`getSumXSquared()` Get sun of the square
`double`	`getSxx()` Get Sxx value: sumXsquared - sumX * sumX / n
`double`	`getSyy()` Get SYY value: sumYsquared - sumY * sumY / n
`double`	`getXBar()` Get average x
`double`	`getYBar()` Get average Y
`void`	`reset()` reset data to 0

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

- Constructor Detail
  - LinReg
```
public LinReg(double[] aX,
              double[] aY)
```
    Constructor for regression calculations
    
    Parameters:
    
    aX - is the array of x data
    
    aY - is the array of y data
  - LinReg
```
public LinReg(P1D aXY)
```
    constructor for regression calculations. It should be noted that only X and Y values from the input P1D data holder are used
    
    Parameters:
    
    aXY - P1D container for X and Y values
- Method Detail
  - reset
```
public void reset()
```
    reset data to 0
  - getCorrelation
```
public double getCorrelation()
```
    Get correlation coefficient
    
    Returns:
    
    Correlation coefficient.
  - getIntercept
```
public double getIntercept()
```
    Get Intercept
    
    Returns:
    
    Intercept
  - getInterceptError
```
public double getInterceptError()
```
    Get the standard error on intercept
    
    Returns:
    
    standard error on intercept
  - getSlopeError
```
public double getSlopeError()
```
    Get the standard error on slope
    
    Returns:
    
    standard error on slope
  - getSlope
```
public double getSlope()
```
    Get slope
    
    Returns:
    
    slope
  - getResiduals
```
public P1D getResiduals()
```
    Get residuals
    
    Returns:
    
    P1D array with residuals
  - getDataX
```
public double[] getDataX()
```
    Get an array with X data
    
    Returns:
    
    array with X data
  - getDataY
```
public double[] getDataY()
```
    Get an array with Y data
    
    Returns:
    
    array with Y data
  - addPoint
```
public void addPoint(double xValue,
                     double yValue)
```
    Add a point to the data and redo the regression
    
    Parameters:
    
    xValue - X value
    
    yValue - Y value
  - getMinX
```
public double getMinX()
```
    Get a minimum value for X
    
    Returns:
    
    Minimum value
  - getMaxX
```
public double getMaxX()
```
    Get a maximum value for X
    
    Returns:
    
    Max value in X
  - getMinY
```
public double getMinY()
```
    Get minimum value for Y
    
    Returns:
    
    minimum Y value
  - getMaxY
```
public double getMaxY()
```
    Get maximum value in Y
    
    Returns:
    
    Maximum value in Y
  - getMaxAbsoluteResidual
```
public double getMaxAbsoluteResidual()
```
    Get max absolute residual
    
    Returns:
    
    max absolute residual
  - getSxx
```
public double getSxx()
```
    Get Sxx value: sumXsquared - sumX * sumX / n
    
    Returns:
    
    Sxx
  - getSyy
```
public double getSyy()
```
    Get SYY value: sumYsquared - sumY * sumY / n
    
    Returns:
    
    Syy valye
  - getSSR
```
public double getSSR()
```
    Ger SSR value
    
    Returns:
    
    SSR value
  - getSSE
```
public double getSSE()
```
    Get SSE value
    
    Returns:
    
    SSE value
  - getMSE
```
public double getMSE()
```
    Get MSE value
    
    Returns:
    
    MSE value
  - getXBar
```
public double getXBar()
```
    Get average x
    
    Returns:
    
    average X
  - getYBar
```
public double getYBar()
```
    Get average Y
    
    Returns:
    
    average Y
  - getDataLength
```
public int getDataLength()
```
    Get the size of the input data
    
    Returns:
    
    size of data array
  - getPearsonR
```
public double getPearsonR()
```
    Get pearson R
    
    Returns:
    
    pearson R
  - getSumXSquared
```
public double getSumXSquared()
```
    Get sun of the square
    
    Returns:
    
    sum of the square
  - getResult
```
public F1D getResult()
```
    Get the linear regression result
    
    Returns:
    
    Resulting function
  - getConfidence
```
public P1D[] getConfidence()
```
    Get confidence intervals for means
    
    Returns:
    
    P1D[2] for lower and high
  - getConfidence
```
public P1D[] getConfidence(java.awt.Color color)
```
    Get confidence intervals for means
    
    Parameters:
    
    color - color used to draw
    
    Returns:
    
    P1D[2] for lower and high
  - getPrediction
```
public P1D[] getPrediction()
```
    Get prediction lines
    
    Returns:
    
    P1D[2] for lower and high
  - getPrediction
```
public P1D[] getPrediction(java.awt.Color color)
```
    Get prediction lines
    
    Parameters:
    
    color - color used to draw
    
    Returns:
    
    P1D[2] for lower and high
  - getConfidenceBand
```
public P1D getConfidenceBand(java.awt.Color color,
                             double transparency)
```
    Calculate confidence band in form of P1D with errors. The number of total points for P1D is set to 100 by default.
    
    Parameters:
    
    color - Color used to show the band
    
    transparancy - level of color transparency (between 0 and 1)
    
    Returns:
    
    P1D with fit values. Errors show the confidence band
  - getConfidenceBand
```
public P1D getConfidenceBand(int Npoints,
                             java.awt.Color color,
                             double transparency)
```
    Calculate confidence band in form of P1D with errors.
    
    Parameters:
    
    Npoints - number of points to display the band
    
    color - Color used to show the band
    
    transparancy - level of color transparency (between 0 and 1)
    
    Returns:
    
    P1D with fit values. Errors show the confidence band
  - getPredictionBand
```
public P1D getPredictionBand()
```
    Calculate the prediction band in form of P1D with errors. The number of total points for P1D is set to 100 by default.
    
    Returns:
    
    P1D with fit values. Errors show the prediction band
  - getPredictionBand
```
public P1D getPredictionBand(java.awt.Color color)
```
    Calculate the prediction band in form of P1D with errors. The number of total points for P1D is set to 100 by default.
    
    Parameters:
    
    color - Color used to show the band
    
    Returns:
    
    P1D with fit values. Errors show the prediction band
  - getPredictionBand
```
public P1D getPredictionBand(java.awt.Color color,
                             double transparency)
```
    Calculate the prediction band in form of P1D with errors. The number of total points for P1D is set to 100 by default.
    
    Parameters:
    
    color - Color used to show the band
    
    transparancy - level of color transparency (between 0 and 1)
    
    Returns:
    
    P1D with fit values. Errors show the prediction band
  - getPredictionBand
```
public P1D getPredictionBand(int Npoints,
                             java.awt.Color color,
                             double transparency)
```
    Calculate the prediction band in form of P1D with errors.
    
    Parameters:
    
    Npoints - number of points for evaluation
    
    color - Color used to show the band
    
    transparancy - level of color transparency (between 0 and 1)
    
    Returns:
    
    P1D with fit values. Errors show the prediction band
  - doc
```
public void doc()
```
    Show online documentation.

Class LinReg

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

LinReg

LinReg

Method Detail

reset

getCorrelation

getIntercept

getInterceptError

getSlopeError

getSlope

getResiduals

getDataX

getDataY

addPoint

getMinX

getMaxX

getMinY

getMaxY

getMaxAbsoluteResidual

getSxx

getSyy

getSSR

getSSE

getMSE

getXBar

getYBar

getDataLength

getPearsonR

getSumXSquared

getResult

getConfidence

getConfidence

getPrediction

getPrediction

getConfidenceBand

getConfidenceBand

getPredictionBand

getPredictionBand

getPredictionBand

getPredictionBand

doc