Package org.elasticsearch.search.aggregations.pipeline.movavg.models

Class HoltLinearModel

java.lang.Object

org.elasticsearch.search.aggregations.pipeline.movavg.models.MovAvgModel

org.elasticsearch.search.aggregations.pipeline.movavg.models.HoltLinearModel

All Implemented Interfaces:

NamedWriteable, Writeable, ToXContent, ToXContentFragment

public class HoltLinearModel
extends MovAvgModel

Calculate a doubly exponential weighted moving average

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	HoltLinearModel.HoltLinearModelBuilder

Nested classes/interfaces inherited from class org.elasticsearch.search.aggregations.pipeline.movavg.models.MovAvgModel

MovAvgModel.AbstractModelParser

Nested classes/interfaces inherited from interface org.elasticsearch.common.xcontent.ToXContent

ToXContent.DelegatingMapParams, ToXContent.MapParams, ToXContent.Params

Nested classes/interfaces inherited from interface org.elasticsearch.common.io.stream.Writeable

Writeable.Reader<V>, Writeable.Writer<V>

Field Summary

Fields

Modifier and Type	Field	Description
static double	DEFAULT_ALPHA
static double	DEFAULT_BETA
static java.lang.String	NAME
static MovAvgModel.AbstractModelParser	PARSER

Fields inherited from interface org.elasticsearch.common.xcontent.ToXContent

EMPTY_PARAMS

Constructor Summary

Constructors

Constructor	Description
HoltLinearModel()
HoltLinearModel(double alpha, double beta)
HoltLinearModel(StreamInput in)	Read from a stream.

Method Summary

Modifier and Type	Method	Description
boolean	canBeMinimized()	Returns if the model can be cost minimized.
MovAvgModel	clone()	Clone the model, returning an exact copy
protected <T extends java.lang.Number> double[]	doPredict(java.util.Collection<T> values, int numPredictions)	Predicts the next `n` values in the series, using the smoothing model to generate new values.
boolean	equals(java.lang.Object obj)
java.lang.String	getWriteableName()	Returns the name of the writeable object
int	hashCode()
MovAvgModel	neighboringModel()	Generates a "neighboring" model, where one of the tunable parameters has been randomly mutated within the allowed range.
<T extends java.lang.Number> double	next(java.util.Collection<T> values)	Returns the next value in the series, according to the underlying smoothing model
<T extends java.lang.Number> double[]	next(java.util.Collection<T> values, int numForecasts)	Calculate a Holt-Linear (doubly exponential weighted) moving average
XContentBuilder	toXContent(XContentBuilder builder, ToXContent.Params params)
void	writeTo(StreamOutput out)	Write the model to the output stream

Methods inherited from class org.elasticsearch.search.aggregations.pipeline.movavg.models.MovAvgModel

emptyPredictions, hasValue, minimizeByDefault, predict

Methods inherited from class java.lang.Object

finalize, getClass, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.elasticsearch.common.xcontent.ToXContentFragment

isFragment

Field Detail

NAME

public static final java.lang.String NAME

See Also:

Constant Field Values

DEFAULT_ALPHA

public static final double DEFAULT_ALPHA

See Also:

Constant Field Values

DEFAULT_BETA

public static final double DEFAULT_BETA

See Also:

Constant Field Values

PARSER

public static final MovAvgModel.AbstractModelParser PARSER

Constructor Detail

HoltLinearModel

public HoltLinearModel()

HoltLinearModel

public HoltLinearModel(double alpha,
                       double beta)

HoltLinearModel

public HoltLinearModel(StreamInput in)
                throws java.io.IOException

Read from a stream.

Throws:

java.io.IOException

Method Detail

writeTo

public void writeTo(StreamOutput out)
             throws java.io.IOException

Description copied from class: MovAvgModel

Write the model to the output stream

Specified by:

writeTo in interface Writeable

Specified by:

writeTo in class MovAvgModel

Parameters:

out - Output stream

Throws:

java.io.IOException

getWriteableName

public java.lang.String getWriteableName()

Description copied from interface: NamedWriteable

Returns the name of the writeable object

canBeMinimized

public boolean canBeMinimized()

Description copied from class: MovAvgModel

Returns if the model can be cost minimized. Not all models have parameters which can be tuned / optimized.

Specified by:

canBeMinimized in class MovAvgModel

neighboringModel

public MovAvgModel neighboringModel()

Description copied from class: MovAvgModel

Generates a "neighboring" model, where one of the tunable parameters has been randomly mutated within the allowed range. Used for minimization

Specified by:

neighboringModel in class MovAvgModel

clone

public MovAvgModel clone()

Description copied from class: MovAvgModel

Clone the model, returning an exact copy

Specified by:

clone in class MovAvgModel

doPredict

protected <T extends java.lang.Number> double[] doPredict(java.util.Collection<T> values,
                                                          int numPredictions)

Predicts the next `n` values in the series, using the smoothing model to generate new values. Unlike the other moving averages, Holt-Linear has forecasting/prediction built into the algorithm. Prediction is more than simply adding the next prediction to the window and repeating. Holt-Linear will extrapolate into the future by applying the trend information to the smoothed data.

Specified by:

doPredict in class MovAvgModel

Type Parameters:

T - Type of numeric

Parameters:

values - Collection of numerics to movingAvg, usually windowed

numPredictions - Number of newly generated predictions to return

Returns:

Returns an array of doubles, since most smoothing methods operate on floating points

next

public <T extends java.lang.Number> double next(java.util.Collection<T> values)

Description copied from class: MovAvgModel

Returns the next value in the series, according to the underlying smoothing model

Specified by:

next in class MovAvgModel

Type Parameters:

T - Type of numeric

Parameters:

values - Collection of numerics to movingAvg, usually windowed

Returns:

Returns a double, since most smoothing methods operate on floating points

next

public <T extends java.lang.Number> double[] next(java.util.Collection<T> values,
                                                  int numForecasts)

Calculate a Holt-Linear (doubly exponential weighted) moving average

Type Parameters:

T - Type T extending Number

Parameters:

values - Collection of values to calculate avg for

numForecasts - number of forecasts into the future to return

Returns:

Returns a Double containing the moving avg for the window

toXContent

public XContentBuilder toXContent(XContentBuilder builder,
                                  ToXContent.Params params)
                           throws java.io.IOException

Throws:

java.io.IOException

hashCode

public int hashCode()

Specified by:

hashCode in class MovAvgModel

equals

public boolean equals(java.lang.Object obj)

Specified by:

equals in class MovAvgModel