Class NodeMetrics.Types.EWMA

The exponentially weighted moving average (EWMA) approach captures short-term movements in volatility for a conditional volatility forecasting model. By virtue of its alpha, or decay factor, this provides a statistical streaming data model that is exponentially biased towards newer entries.

http://en.wikipedia.org/wiki/Moving_average#Exponential_moving_average

An EWMA only needs the most recent forecast value to be kept, as opposed to a standard moving average model.

Parameter 'alpha' decay factor, sets how quickly the exponential weighting decays for past data compared to new data, see http://en.wikipedia.org/wiki/Moving_average#Exponential_moving_average

Parameter 'value' the current exponentially weighted moving average, e.g. Y(n - 1), or, the sampled value resulting from the previous smoothing iteration. This value is always used as the previous EWMA to calculate the new EWMA.

Inheritance
Object
NodeMetrics.Types.EWMA
Implements
Inherited Members
Namespace: Akka.Cluster.Metrics.Serialization
Assembly: Akka.Cluster.Metrics.dll
Syntax
public sealed class EWMA : IEquatable<NodeMetrics.Types.EWMA>

Constructors

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EWMA(Double, Double)

Creates new instance of NodeMetrics.Types.EWMA

Declaration
public EWMA(double value, double alpha)
Parameters
Type Name Description
Double value

The current exponentially weighted moving average, e.g. Y(n - 1), or, the sampled value resulting from the previous smoothing iteration.
Double alpha

Decay factor, sets how quickly the exponential weighting decays for past data compared to new data, see http://en.wikipedia.org/wiki/Moving_average#Exponential_moving_average

Properties

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Alpha

Declaration
public double Alpha { get; }
Property Value
Type Description
Double
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Value

Declaration
public double Value { get; }
Property Value
Type Description
Double

Methods

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Equals(NodeMetrics.Types.EWMA)

Declaration
public bool Equals(NodeMetrics.Types.EWMA other)
Parameters
Type Name Description
NodeMetrics.Types.EWMA other
Returns
Type Description
Boolean
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Equals(Object)

Declaration
public override bool Equals(object obj)
Parameters
Type Name Description
Object obj
Returns
Type Description
Boolean
Overrides
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GetAlpha(TimeSpan, TimeSpan)

Calculate the alpha (decay factor) used in [[akka.cluster.EWMA]] from specified half-life and interval between observations. Half-life is the interval over which the weights decrease by a factor of two. The relevance of each data sample is halved for every passing half-life duration, i.e. after 4 times the half-life, a data sample’s relevance is reduced to 6% of its original relevance. The initial relevance of a data sample is given by 1 – 0.5 ^ (collect-interval / half-life).

Declaration
public static double GetAlpha(TimeSpan halfLife, TimeSpan collectInterval)
Parameters
Type Name Description
TimeSpan halfLife
TimeSpan collectInterval
Returns
Type Description
Double
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GetHashCode()

Declaration
public override int GetHashCode()
Returns
Type Description
Int32
Overrides

Operators

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Addition(NodeMetrics.Types.EWMA, Double)

Calculates the exponentially weighted moving average for a given monitored data set.

Declaration
public static NodeMetrics.Types.EWMA operator +(NodeMetrics.Types.EWMA current, double xn)
Parameters
Type Name Description
NodeMetrics.Types.EWMA current

Current EWMA value
Double xn

The new data point
Returns
Type Description
NodeMetrics.Types.EWMA

A new EWMA with the updated value

Implements

Extension Methods