pamMaths

## Class Regressions

• java.lang.Object
• pamMaths.Regressions

• ```public class Regressions
extends java.lang.Object```
Class for performing various regressions. Relies heavily on the Matrixes and other utilities in the JAMA package. Developers must download JAMA and install the jar file into their JAVA path.

see http://math.nist.gov/javanumerics/jama/

Author:
Douglas Gillespie
• ### Constructor Summary

Constructors
Constructor and Description
`Regressions()`
• ### Method Summary

Methods
Modifier and Type Method and Description
`static double` `getMean(double[] y)`
Get the mean of a set of values
`static double[]` ```linFit(double[] x, double[] y)```
Fit a linear regression line to a set of points
`static double[]` `meanFit(double[] y)`
Return the mean of a set of points as a one element array for compatibility with other, higher order fits.
`static double[]` ```polyFit(double[] x, double[] y, int order)```
`static double[]` ```squareFit(double[] x, double[] y)```
Fit a second order polynomial to a set of points
`static double` ```value(double[] fitParams, double x)```
Use the parameters of the fit to calculate a value using the fitParams polynomial.
• ### Methods inherited from class java.lang.Object

`equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`
• ### Constructor Detail

• #### Regressions

`public Regressions()`
• ### Method Detail

• #### polyFit

```public static double[] polyFit(double[] x,
double[] y,
int order)```
• #### meanFit

`public static double[] meanFit(double[] y)`
Return the mean of a set of points as a one element array for compatibility with other, higher order fits.
Parameters:
`y` - array ofvalues
Returns:
the mean value as a one element array
• #### getMean

`public static double getMean(double[] y)`
Get the mean of a set of values
Parameters:
`y` - array ofvalues
Returns:
the mean value
• #### linFit

```public static double[] linFit(double[] x,
double[] y)```
Fit a linear regression line to a set of points
Parameters:
`x` - array of x coordinates
`y` - array of y coordinates
Returns:
the two coefficients for the fit
• #### squareFit

```public static double[] squareFit(double[] x,
double[] y)```
Fit a second order polynomial to a set of points
Parameters:
`x` - array of x coordinates
`y` - array of y coordinates
Returns:
the three coefficients for the fit or null if a fit is not possible.
• #### value

```public static double value(double[] fitParams,
double x)```
Use the parameters of the fit to calculate a value using the fitParams polynomial.
Parameters:
`fitParams` - parameters of the fit
`x` - x value
Returns:
y value = fitParams[0] + fitParams[1]*x + fitParams[2]*x^2, etc...