RunningStatistics2D (galileo 1.6 Documentation)

java.lang.Object
- galileo.stat.RunningStatistics2D

All Implemented Interfaces:

galileo.serialization.ByteSerializable
```
public class RunningStatistics2D
extends java.lang.Object
implements galileo.serialization.ByteSerializable
```
Expanding on the RunningStatistics class, this class supports two dimensions (x and y), along with some extra features (simple linear regression, r^2, calculating correlation).

Author:

malensek

Nested Class Summary

Nested Classes
Modifier and Type	Class and Description
`class`	`RunningStatistics2D.PearsonResult` Encapsulates the results of a Pearson product-moment correlation coefficient calculation, including the two-tailed p-value.

Nested classes/interfaces inherited from interface galileo.serialization.ByteSerializable
galileo.serialization.ByteSerializable.Deserialize

Constructor Summary

Constructors
Constructor and Description

RunningStatistics2D()

RunningStatistics2D(galileo.serialization.SerializationInputStream in)

Constructors
Constructor and Description
`RunningStatistics2D()`
`RunningStatistics2D(galileo.serialization.SerializationInputStream in)`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`double`	`intercept()`
`void`	`merge(RunningStatistics2D that)`
`long`	`n()` Retrieves the number of samples submitted to the RunningStatistics2D instance so far.
`double`	`predict(double x)` Given a value of x, estimate the outcome of y using simple linear regression.
`void`	`put(double[]... samples)` Adds several new (x, y) sample pairs to the 2D running statistics.
`void`	`put(double x, double y)` Adds a new sample to the 2D running statistics.
`double`	`r()` Calculate the Pearson product-moment correlation coefficient.
`double`	`r2()` Calculate the coefficient of determination (r squared).
`RunningStatistics2D.PearsonResult`	`rp()` Calculate the Pearson product-moment correlation coefficient, including the two-tailed p-value.
`void`	`serialize(galileo.serialization.SerializationOutputStream out)`
`double`	`slope()`
`double`	`SSxx()`
`double`	`SSxy()`
`double`	`SSyy()`
`RunningStatistics`	`xStat()`
`RunningStatistics`	`yStat()`

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

- Constructor Detail
  - RunningStatistics2D
```
public RunningStatistics2D()
```
  - RunningStatistics2D
```
@ByteSerializable.Deserialize
public RunningStatistics2D(galileo.serialization.SerializationInputStream in)
                                                  throws java.io.IOException
```
    Throws:
    
    java.io.IOException
- Method Detail
  - merge
```
public void merge(RunningStatistics2D that)
```
  - put
```
public void put(double[]... samples)
```
    Adds several new (x, y) sample pairs to the 2D running statistics.
    
    Parameters:
    
    samples - Array of two-element arrays (representing x and y)
  - put
```
public void put(double x,
                double y)
```
    Adds a new sample to the 2D running statistics.
  - SSxy
```
public double SSxy()
```
    Returns:
    
    Sum of the cross products (xy)
  - SSxx
```
public double SSxx()
```
    Returns:
    
    Sum of squared deviations from the mean of x
  - SSyy
```
public double SSyy()
```
    Returns:
    
    Sum of squared deviations from the mean of y
  - r
```
public double r()
```
    Calculate the Pearson product-moment correlation coefficient.
    
    Returns:
    
    PPMCC (Pearson's r)
  - rp
```
public RunningStatistics2D.PearsonResult rp()
```
    Calculate the Pearson product-moment correlation coefficient, including the two-tailed p-value.
    
    Returns:
    
    PearsonResult containing the r-value and two-tailed p-value.
  - r2
```
public double r2()
```
    Calculate the coefficient of determination (r squared).
    
    Returns:
    
    coefficient of determination
  - slope
```
public double slope()
```
    Returns:
    
    the slope of the regression line (beta).
  - intercept
```
public double intercept()
```
    Returns:
    
    the y-intercept of the regression line (alpha).
  - predict
```
public double predict(double x)
```
    Given a value of x, estimate the outcome of y using simple linear regression.
    
    Returns:
    
    estimated value of y
  - xStat
```
public RunningStatistics xStat()
```
    Returns:
    
    a copy of the running statistics instance for x.
  - yStat
```
public RunningStatistics yStat()
```
    Returns:
    
    a copy of the running statistics instance for y.
  - n
```
public long n()
```
    Retrieves the number of samples submitted to the RunningStatistics2D instance so far.
    
    Returns:
    
    number of samples
  - serialize
```
public void serialize(galileo.serialization.SerializationOutputStream out)
               throws java.io.IOException
```
    Specified by:
    
    serialize in interface galileo.serialization.ByteSerializable
    
    Throws:
    
    java.io.IOException

Class RunningStatistics2D

Nested Class Summary

Nested classes/interfaces inherited from interface galileo.serialization.ByteSerializable

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

RunningStatistics2D

RunningStatistics2D

Method Detail

merge

put

put

SSxy

SSxx

SSyy

r

rp

r2

slope

intercept

predict

xStat

yStat

n

serialize