de.lmu.ifi.dbs.elki.math

Class Mean

java.lang.Object

de.lmu.ifi.dbs.elki.math.Mean

Direct Known Subclasses:

MeanVariance

@Reference(authors="B. P. Welford",
           title="Note on a method for calculating corrected sums of squares and products",
           booktitle="Technometrics 4(3)")
public class Mean
extends Object

Compute the mean using a numerically stable online algorithm. This class can repeatedly be fed with data using the add() methods, the resulting values for mean can be queried at any time using getMean(). Trivial code, but replicated a lot. The class is final so it should come at low cost. Related Literature:

B. P. Welford
Note on a method for calculating corrected sums of squares and products
in: Technometrics 4(3)

D.H.D. West
Updating Mean and Variance Estimates: An Improved Method
In: Communications of the ACM, Volume 22 Issue 9

Author:

Erich Schubert

Field Summary

Fields

Modifier and Type	Field and Description
protected double	m1 Mean of values - first moment.
protected double	n Weight sum (number of samples).

Constructor Summary

Constructors

Constructor and Description
Mean() Empty constructor
Mean(Mean other) Constructor from other instance

Method Summary

Methods

Modifier and Type	Method and Description
double	getCount() Get the number of points the average is based on.
double	getMean() Return mean
static Mean[]	newArray(int dimensionality) Create and initialize a new array of MeanVariance
static double	of(double[] data) Static helper function.
void	put(double val) Add a single value with weight 1.0
Mean	put(double[] vals) Add values with weight 1.0
Mean	put(double[] vals, double[] weights) Add values with weight 1.0
void	put(double val, double weight) Add data with a given weight.
void	put(Mean other) Join the data of another MeanVariance instance.
void	reset() Reset the value.
String	toString()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

m1

protected double m1

Mean of values - first moment.

n

protected double n

Weight sum (number of samples).

Constructor Detail

Mean

public Mean()

Empty constructor

Mean

public Mean(Mean other)

Constructor from other instance

Parameters:

other - other instance to copy data from.

Method Detail

put

public void put(double val)

Add a single value with weight 1.0

Parameters:

val - Value

put

public void put(double val,
       double weight)

Add data with a given weight. See also: D.H.D. West
Updating Mean and Variance Estimates: An Improved Method

Parameters:

val - data

weight - weight

put

public void put(Mean other)

Join the data of another MeanVariance instance.

Parameters:

other - Data to join with

put

public Mean put(double[] vals)

Add values with weight 1.0

Parameters:

vals - Values

Returns:

this

put

public Mean put(double[] vals,
       double[] weights)

Add values with weight 1.0

Parameters:

vals - Values

Returns:

this

getCount

public double getCount()

Get the number of points the average is based on.

Returns:

number of data points

getMean

public double getMean()

Return mean

Returns:

mean

newArray

public static Mean[] newArray(int dimensionality)

Create and initialize a new array of MeanVariance

Parameters:

dimensionality - Dimensionality

Returns:

New and initialized Array

toString

public String toString()

Overrides:

toString in class Object

reset

public void reset()

Reset the value.

of

public static double of(double[] data)

Static helper function.

Parameters:

data - Data to compute the mean for.

Returns:

Mean