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

Class HoltWintersModel

    • 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

      • 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 double[] doPredict​(java.util.Collection<java.lang.Double> 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
        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 double next​(java.util.Collection<java.lang.Double> 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
        Parameters:
        values - Collection of numerics to movingAvg, usually windowed
        Returns:
        Returns a double, since most smoothing methods operate on floating points

      • next

        public double[] next​(java.util.Collection<java.lang.Double> values,
                     int numForecasts)
        Calculate a doubly exponential weighted moving average
        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

      • equals

        public boolean equals​(java.lang.Object obj)
        Specified by:
        equals in class MovAvgModel