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.

2.0

Hierarchy (view full)

Implements

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

    2.0

  • set AllowEmptyValueReplacement(value): 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): 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): void
  • Parameters

    • value: number

    Returns void

  • get Context(): INodeContext
  • Gets the context of this node.

    Returns INodeContext

    2.0

  • 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): 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): void
  • Parameters

    • value: string

    Returns void

  • get IndividualFittingModes(): IndividualFittingModes
  • The visualization features to calculate curves for. Features may be combined, which will result in one curve per combination.

    Returns IndividualFittingModes

    2.0

  • set IndividualFittingModes(value): void
  • Parameters

    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): 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): 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): 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): 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): 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): 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): void
  • Parameters

    • value: boolean

    Returns void