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

クラス HoltWintersModel

java.lang.Object

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

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

public class HoltWintersModel
extends MovAvgModel

Calculate a triple exponential weighted moving average

ネストされたクラスのサマリー

ネストされたクラス

修飾子とタイプ	クラスと説明
static class	HoltWintersModel.HoltWintersModelBuilder
static class	HoltWintersModel.HoltWintersModelParser
static class	HoltWintersModel.SeasonalityType

クラスから継承されたネストされたクラス/インタフェース org.elasticsearch.search.aggregations.pipeline.movavg.models.MovAvgModel

MovAvgModel.AbstractModelParser

フィールドのサマリー

フィールド

修飾子とタイプ	フィールドと説明
protected static ParseField	NAME_FIELD
static MovAvgModelStreams.Stream	STREAM

コンストラクタのサマリー

コンストラクタ

コンストラクタと説明
HoltWintersModel(double alpha, double beta, double gamma, int period, HoltWintersModel.SeasonalityType seasonalityType, boolean pad)

メソッドのサマリー

修飾子とタイプ	メソッドと説明
boolean	canBeMinimized() Returns if the model can be cost minimized.
MovAvgModel	clone() Clone the model, returning an exact copy
protected <T extends Number> double[]	doPredict(Collection<T> values, int numPredictions) Predicts the next `n` values in the series, using the smoothing model to generate new values.
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 Number> double	next(Collection<T> values) Returns the next value in the series, according to the underlying smoothing model
<T extends Number> double[]	next(Collection<T> values, int numForecasts) Calculate a doubly exponential weighted moving average
void	writeTo(StreamOutput out) Write the model to the output stream

クラスから継承されたメソッド org.elasticsearch.search.aggregations.pipeline.movavg.models.MovAvgModel

emptyPredictions, predict

クラスから継承されたメソッド java.lang.Object

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

フィールドの詳細

NAME_FIELD

protected static final ParseField NAME_FIELD

STREAM

public static final MovAvgModelStreams.Stream STREAM

コンストラクタの詳細

HoltWintersModel

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

メソッドの詳細

minimizeByDefault

public boolean minimizeByDefault()

クラスからコピーされた説明: MovAvgModel

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

オーバーライド:

minimizeByDefault クラス内 MovAvgModel

canBeMinimized

public boolean canBeMinimized()

クラスからコピーされた説明: MovAvgModel

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

定義:

canBeMinimized クラス内 MovAvgModel

neighboringModel

public MovAvgModel neighboringModel()

クラスからコピーされた説明: MovAvgModel

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

定義:

neighboringModel クラス内 MovAvgModel

clone

public MovAvgModel clone()

クラスからコピーされた説明: MovAvgModel

Clone the model, returning an exact copy

定義:

clone クラス内 MovAvgModel

hasValue

public boolean hasValue(int valuesAvailable)

クラスからコピーされた説明: 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

オーバーライド:

hasValue クラス内 MovAvgModel

パラメータ:

valuesAvailable - Number of values in the current window of values

戻り値:

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

doPredict

protected <T extends Number> double[] doPredict(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.

定義:

doPredict クラス内 MovAvgModel

型パラメータ:

T - Type of numeric

パラメータ:

values - Collection of numerics to movingAvg, usually windowed

numPredictions - Number of newly generated predictions to return

戻り値:

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

next

public <T extends Number> double next(Collection<T> values)

クラスからコピーされた説明: MovAvgModel

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

定義:

next クラス内 MovAvgModel

型パラメータ:

T - Type of numeric

パラメータ:

values - Collection of numerics to movingAvg, usually windowed

戻り値:

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

next

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

Calculate a doubly exponential weighted moving average

型パラメータ:

T - Type T extending Number

パラメータ:

values - Collection of values to calculate avg for

numForecasts - number of forecasts into the future to return

戻り値:

Returns a Double containing the moving avg for the window

writeTo

public void writeTo(StreamOutput out)
             throws IOException

クラスからコピーされた説明: MovAvgModel

Write the model to the output stream

定義:

writeTo クラス内 MovAvgModel

パラメータ:

out - Output stream

例外:

IOException