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    Class ForecastHoltWintersFittingModel

    A model contining the parameters for a Holt-Winters forecast. Usually applied to time series data, but it can be used with any discrete set of repeated measurements.

    This class cannot be inherited. See the Spotfire.Dxp.Application.Extension.CustomFittingModel class for creating custom fitting models.

    2.0

    Hierarchy (View Summary)

    Implements

    Index

    Methods

    Cast Equals GetHashCode ToString TryCast Equals

    Default capability

    AllowEmptyValueReplacement AutomaticFrequency ConfidenceCurve ConfidenceLevel Context Enabled FittedCurve ForecastCurve Frequency FrequencyExpression IndividualFittingModes IsAttached Level ManualUpdate Seasonal SeasonalModelType TimePointsAhead TimePointsAheadExpression Transactions Trend TypeId UseSeasonal UseTrend GetResultsDataSource Update

    Methods

    • Casts this object to the specified type. Throws error on failure.

      Type Parameters

      • T1

        The target type of the cast.

      • T2

        The type of the object to cast.

      Parameters

      Returns T1

    • Determines whether the specified object is equal to the current object.

      Parameters

      • obj: any

        The object to compare with the current object.

      Returns boolean

      true if the specified object is equal to the current object; otherwise, false.

    • Serves as the default hash function.

      Returns number

      A hash code for the current object.

    • Returns a string that represents the current object.

      Returns string

      A string that represents the current object.

    • Casts this object to the specified type. Returns null on failure.

      Type Parameters

      • T1

        The target type of the cast.

      • T2

        The type of the object to cast.

      Parameters

      Returns null | T1

    • Determines whether the specified object instances are considered equal.

      Parameters

      • objA: any

        The first object to compare.

      • objB: any

        The second object to compare.

      Returns boolean

      true if the objects are considered equal; otherwise, false. If both objA and objB are null, the method returns true.

    Default capability

    • get AllowEmptyValueReplacement(): boolean

      Gets or sets a value indicating whether this Holt Winters model allows interpolation to replace missing values. Setting this to true will mean that an empty value in the time series will be replaced by linear interpolation between the values before and after it. If there are multiple empty values in a row then no curve fit is computed. Setting this value to false will mean that if empty values are found in the time series, no curve fit is computed.

      Returns boolean

      Empty values at the start and end of the time series are always trimmed.

      2.0

    • set AllowEmptyValueReplacement(value: boolean): void

      Parameters

      • value: boolean

      Returns void

    • get AutomaticFrequency(): boolean

      Gets or sets a value indicating whether the frequency parameter is deduced from the visualization.

      Returns boolean

      2.0

    • set AutomaticFrequency(value: boolean): void

      Parameters

      • value: boolean

      Returns void

    • get ConfidenceLevel(): number

      Gets or sets the confidence level for the prediction intervals. Must be within the half-open unit interval [0, 1), but is typically close to 1.

      Returns number

      2.0

    • set ConfidenceLevel(value: number): void

      Parameters

      • value: number

      Returns void

    • get Context(): INodeContext

      Gets the context of this node.

      Returns INodeContext

      2.0

    • get Enabled(): boolean

      Gets or sets a value indicating whether this Spotfire.Dxp.Application.Visuals.FittingModels.FittingModel is enabled.

      Returns boolean

      2.0

    • set Enabled(value: boolean): void

      Parameters

      • value: boolean

      Returns void

    • get Frequency(): number

      Gets or sets the frequency (the number of observations per sampling period). For example, monthly data have frequency=12. This must be greater than 1 to fit a seasonal component.
      This is a convenience wrapper of Spotfire.Dxp.Application.Visuals.FittingModels.ForecastHoltWintersFittingModel.FrequencyExpression. If this property is read when preprocessor expression does not evaluate to a positive integer, -1 is returned.

      Returns number

      2.0

    • set Frequency(value: number): void

      Parameters

      • value: number

      Returns void

    • get FrequencyExpression(): string

      Gets or sets the frequency expression (the number of observations per sampling period). For example, monthly data have frequency=12. This string is preprocessed and should evaluate to a positive integer. This must be greater than 1 to fit a seasonal component.

      Returns string

      2.0

    • set FrequencyExpression(value: string): void

      Parameters

      • value: string

      Returns void

    • get IsAttached(): boolean

      Gets a value indicating whether this node is attached.

      Returns boolean

      2.0

    • get Level(): null | number

      Gets or sets the level (alpha) parameter of Holt-Winters specifying how to smooth the level component. Must be within the half-open unit interval (0, 1]. A small value means that older values in x are weighted more heavily. Values near 1.0 mean that the latest value has more weight. NULL means that the HoltWinters function should find the optimal value of alpha.

      Returns null | number

      2.0

    • set Level(value: null | number): void

      Parameters

      • value: null | number

      Returns void

    • get ManualUpdate(): boolean

      Gets or sets a value indicating whether to use manual updates.

      Returns boolean

      2.0

    • set ManualUpdate(value: boolean): void

      Parameters

      • value: boolean

      Returns void

    • get Seasonal(): null | number

      Gets or sets the seasonal (gamma) parameter of Holt-Winters specifying how to smooth the seasonal component. Must be within the unit interval [0, 1]. A small value means that older values in x are weighted more heavily. Values near 1.0 mean that the latest value has more weight. NULL means that the HoltWinters function should find the optimal value of gamma.

      Returns null | number

      2.0

    • set Seasonal(value: null | number): void

      Parameters

      • value: null | number

      Returns void

    • get TimePointsAheadExpression(): string

      Gets or sets the number of time points in the future at which to predict the values of the time series

      Returns string

      2.0

    • set TimePointsAheadExpression(value: string): void

      Parameters

      • value: string

      Returns void

    • get Transactions(): ITransactions

      Gets a collection of methods for executing transactions on the document.

      Returns ITransactions

      2.0

    • get Trend(): null | number

      Gets or sets the trend (beta) parameter of Holt-Winters specifying how to smooth the trend component. Must be within the unit interval [0, 1]. A small value means that older values in x are weighted more heavily. Values near 1.0 mean that the latest value has more weight. NULL means that the HoltWinters function should find the optimal value of beta.

      Returns null | number

      2.0

    • set Trend(value: null | number): void

      Parameters

      • value: null | number

      Returns void

    • get UseSeasonal(): boolean

      Gets or sets a value indicating whether the seasonal component should be included or not.

      Returns boolean

      2.0

    • set UseSeasonal(value: boolean): void

      Parameters

      • value: boolean

      Returns void

    • get UseTrend(): boolean

      Gets or sets a value indicating whether the trend component should be included or not.

      Returns boolean

      2.0

    • set UseTrend(value: boolean): void

      Parameters

      • value: boolean

      Returns void

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