Covariance

java.lang.Object
- com.itemanalysis.psychometrics.polycor.Covariance

All Implemented Interfaces:: java.lang.Comparable<Covariance>

public class Covariance
extends java.lang.Object
implements java.lang.Comparable<Covariance>

Author:: J. Patrick Meyer

Constructor Summary

Constructors
Constructor and Description
`Covariance()`
`Covariance(boolean unbiased)`
`Covariance(Covariance cov)`
`Covariance(Covariance cov, boolean unbiased)`
`Covariance(double covariance)`
`Covariance(double covariance, boolean unbiased)`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`int`	`compareTo(Covariance that)`
`double`	`correlation()`
`double`	`correlationPvalue()`
`double`	`correlationStandardError()`
`boolean`	`equals(java.lang.Object obj)`
`int`	`hashCode()`
`void`	`increment(java.lang.Double x, java.lang.Double y)` Update formula for recursive on-line (i.e.
`double`	`sampleSize()`
`double`	`sdX()`
`double`	`sdY()`
`double`	`value()`
`double`	`varX()`
`double`	`varY()`

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

- Constructor Detail
  - Covariance
```
public Covariance(boolean unbiased)
```
  - Covariance
```
public Covariance()
```
  - Covariance
```
public Covariance(double covariance,
                  boolean unbiased)
```
  - Covariance
```
public Covariance(double covariance)
```
  - Covariance
```
public Covariance(Covariance cov,
                  boolean unbiased)
```
  - Covariance
```
public Covariance(Covariance cov)
```
- Method Detail
  - increment
```
public void increment(java.lang.Double x,
                      java.lang.Double y)
```
    Update formula for recursive on-line (i.e. one pass) method of computing the covariance.This method is given by XXXX. It is an extension of the on-line mean and variance algorithms by Knuth (1998) and Welford (1962). It is more numerically accurate than the computational formula (i.e. naive) for the covariance. The standard deviation algorithms are also more numerically accurate than the computational formula (i.e. naive). Donald E. Knuth (1998). The Art of Computer Programming, volume 2: Seminumerical Algorithms, 3rd edn., p. 232. Boston: Addison-Wesley. B. P. Welford (1962)."Note on a method for calculating corrected sums of squares and products". Technometrics 4(3):419–420.
    
    Parameters:
    
    x -
    
    y -
  - value
```
public double value()
```
  - varX
```
public double varX()
```
  - sdX
```
public double sdX()
```
  - varY
```
public double varY()
```
  - sdY
```
public double sdY()
```
  - correlation
```
public double correlation()
```
  - correlationStandardError
```
public double correlationStandardError()
```
  - correlationPvalue
```
public double correlationPvalue()
```
  - sampleSize
```
public double sampleSize()
```
  - compareTo
```
public int compareTo(Covariance that)
```
    Specified by:
    
    compareTo in interface java.lang.Comparable<Covariance>
  - equals
```
public boolean equals(java.lang.Object obj)
```
    Overrides:
    
    equals in class java.lang.Object
  - hashCode
```
public int hashCode()
```
    Overrides:
    
    hashCode in class java.lang.Object

Class Covariance

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

Covariance

Covariance

Covariance

Covariance

Covariance

Covariance

Method Detail

increment

value

varX

sdX

varY

sdY

correlation

correlationStandardError

correlationPvalue

sampleSize

compareTo

equals

hashCode