xal.tools.statistics

Class RunningWeightedStatistics

java.lang.Object

xal.tools.statistics.UnivariateStatistics

xal.tools.statistics.RunningWeightedStatistics

public class RunningWeightedStatistics
extends UnivariateStatistics

Calculate running statistics using weighted averaging

Field Summary

Fields

Modifier and Type	Field and Description
protected int	ASYMPTOTIC_POPULATION population beyond which we should use the asymptotic weight
protected double	ASYMPTOTIC_WEIGHT weight for new samples

Fields inherited from class xal.tools.statistics.UnivariateStatistics

_mean, _meanSquare, _population

Constructor Summary

Constructors

Constructor and Description
RunningWeightedStatistics(double weight) Constructor

Method Summary

Modifier and Type	Method and Description
void	addSample(double value) Add a new sample measurement.
void	clear() Clear the samples
protected double	getWeight() Get the current weight.
protected double	getWeight(double population) Get the weight to apply to the next new sample given the specified population.
double	sampleVarianceOfMean() Get the variance of the mean from the actual value assuming the supporting data is a random subset of all the data.
double	varianceOfMean() Get the variance of the mean from the actual value.

Methods inherited from class xal.tools.statistics.UnivariateStatistics

mean, meanSquare, population, sampleStandardDeviation, sampleStandardDeviationOfMean, sampleVariance, standardDeviation, standardDeviationOfMean, variance

Methods inherited from class java.lang.Object

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

Field Detail

ASYMPTOTIC_WEIGHT

protected final double ASYMPTOTIC_WEIGHT

weight for new samples

ASYMPTOTIC_POPULATION

protected final int ASYMPTOTIC_POPULATION

population beyond which we should use the asymptotic weight

Constructor Detail

RunningWeightedStatistics

public RunningWeightedStatistics(double weight)

Constructor

Parameters:

weight - asymptotic weight to apply to new samples in large populations

Method Detail

clear

public void clear()

Clear the samples

getWeight

protected final double getWeight()

Get the current weight.

Returns:

the current weight

getWeight

protected final double getWeight(double population)

Get the weight to apply to the next new sample given the specified population. When we first start adding samples, we must trust the newest samples most and gradually shift trust to the older samples. Ultimately we will trust new samples at least at the asymptotic weight.

addSample

public void addSample(double value)

Add a new sample measurement.

Parameters:

value - The new sample measurement

varianceOfMean

public double varianceOfMean()

Get the variance of the mean from the actual value.

Overrides:

varianceOfMean in class UnivariateStatistics

Returns:

the variance of the mean from the actual value

sampleVarianceOfMean

public double sampleVarianceOfMean()

Get the variance of the mean from the actual value assuming the supporting data is a random subset of all the data.

Overrides:

sampleVarianceOfMean in class UnivariateStatistics

Returns:

the sample variance of the mean