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

Class HoltWintersModel

java.lang.Object

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

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

All Implemented Interfaces:

NamedWriteable, Writeable, ToXContent, ToXContentFragment

public class HoltWintersModel
extends MovAvgModel

Calculate a triple exponential weighted moving average

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	HoltWintersModel.HoltWintersModelBuilder
static class	HoltWintersModel.SeasonalityType

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.io.stream.Writeable

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

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

ToXContent.DelegatingMapParams, ToXContent.MapParams, ToXContent.Params

Field Summary

Fields

Modifier and Type	Field and Description
static double	DEFAULT_ALPHA
static double	DEFAULT_BETA
static double	DEFAULT_GAMMA
static boolean	DEFAULT_PAD
static int	DEFAULT_PERIOD
static HoltWintersModel.SeasonalityType	DEFAULT_SEASONALITY_TYPE
static java.lang.String	NAME
static MovAvgModel.AbstractModelParser	PARSER

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

EMPTY_PARAMS

Constructor Summary

Constructors

Constructor and Description
HoltWintersModel()
HoltWintersModel(double alpha, double beta, double gamma, int period, HoltWintersModel.SeasonalityType seasonalityType, boolean pad)
HoltWintersModel(StreamInput in) Read from a stream.

Method Summary

Modifier and Type	Method and 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()
boolean	hasValue(int valuesAvailable) Checks to see this model can produce a new value, without actually running the algo.
boolean	minimizeByDefault() Should this model be fit to the data via a cost minimizing algorithm by default?
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 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, 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

DEFAULT_GAMMA

public static final double DEFAULT_GAMMA

See Also:

Constant Field Values

DEFAULT_PERIOD

public static final int DEFAULT_PERIOD

See Also:

Constant Field Values

DEFAULT_SEASONALITY_TYPE

public static final HoltWintersModel.SeasonalityType DEFAULT_SEASONALITY_TYPE

DEFAULT_PAD

public static final boolean DEFAULT_PAD

See Also:

Constant Field Values

PARSER

public static final MovAvgModel.AbstractModelParser PARSER

Constructor Detail

HoltWintersModel

public HoltWintersModel()

HoltWintersModel

public HoltWintersModel(double alpha,
                        double beta,
                        double gamma,
                        int period,
                        HoltWintersModel.SeasonalityType seasonalityType,
                        boolean pad)

HoltWintersModel

public HoltWintersModel(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

minimizeByDefault

public boolean minimizeByDefault()

Description copied from class: MovAvgModel

Should this model be fit to the data via a cost minimizing algorithm by default?

Overrides:

minimizeByDefault in class MovAvgModel

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

hasValue

public boolean hasValue(int valuesAvailable)

Description copied from class: MovAvgModel

Checks to see this model can produce a new value, without actually running the algo. This can be used for models that have certain preconditions that need to be met in order to short-circuit execution

Overrides:

hasValue in class MovAvgModel

Parameters:

valuesAvailable - Number of values in the current window of values

Returns:

Returns `true` if calling next() will produce a value, `false` otherwise

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, HoltWinters has forecasting/prediction built into the algorithm. Prediction is more than simply adding the next prediction to the window and repeating. HoltWinters will extrapolate into the future by applying the trend and seasonal 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 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