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    • Accumulator(T, U) Class
    • Aggregator(T, U) Class
    • Aggregator2(T, U) Class
    • Aggregator2Group Class
    • Aggregator2Group(T) Class
    • AggregatorGroup Class
    • AggregatorGroup(T) Class
    • Aggregators Class
    • BoundaryIntervalBehavior Enumeration
    • CategoricalEncoding Class
    • DataFrame Class
    • DataFrame(R, C) Class
    • DataFrameRow(R, C) Class
    • DateTimeExtensions Class
    • DateTimeUnit Enumeration
    • Direction Enumeration
    • Grouping Class
    • Grouping(TKey) Class
    • Histogram Class
    • Histogram(T) Class
    • IAccumulator(T, U) Interface
    • IAccumulator2(T, U) Interface
    • IAccumulator2(T, U, V) Interface
    • IAggregator Interface
    • IAggregator(T) Interface
    • IAggregator2 Interface
    • IAggregator2(T) Interface
    • IDataFrame Interface
    • IGrouping Interface
    • IIndex Interface
    • Index Class
    • Index(T) Class
    • IntervalIndex(T) Class
    • IPivot Interface
    • JoinIndex Class
    • JoinType Enumeration
    • MissingValueAction Enumeration
    • MissingValueException Class
    • MultipleMissingValueAction Enumeration
    • Parameter(T) Class
    • ParameterVector(T) Class
    • Pivot Class
    • Pivot(R, C) Class
    • RankTiebreaker Enumeration
    • Recurrence Class
    • SortOrder Enumeration
    • SpecialBins Enumeration
    • Subset Class
    • TransformedParameter(T) Class
    • TypePreservingAggregatorGroup Class
    • VectorExtensions Class
  • VectorExtensions Class
    • Methods
  • Methods
    • ApplyHodrickPrescottFilter Method
    • BoxCoxTransform Method
    • Change Method
    • ExponentialMovingAverage Method Overloads
    • ExtrapolatedChange Method
    • ExtrapolatedGrowthRate Method
    • ExtrapolatedPercentChange Method
    • GrowthRate Method
    • Lag Method Overloads
    • MovingAverage Method Overloads
    • MovingAverageAbsoluteDeviation Method
    • MovingMaximum Method
    • MovingMinimum Method
    • MovingStandardDeviation Method
    • MovingSum Method
    • PercentChange Method
    • PeriodToDateDifferences Method Overloads
    • PeriodToDateValues Method Overloads
    • PositiveToNegativeIndex Method
    • PositiveToNegativeRatio Method
    • Quantile(T) Method
    • Quantiles(T) Method
    • ReferenceIndex Method Overloads
    • UseBackwardDifferenceEncoding Method
    • UseDeviationEncoding Method
    • UseDummyEncoding Method
    • UseForwardDifferenceEncoding Method
    • UseHelmertEncoding Method
    • UseInverseHelmertEncoding Method
    • UsePolynomialEncoding Method
    • UseSimpleEncoding Method
    • WeightedMovingAverage Method Overloads

VectorExtensions Methods

Extreme Optimization Numerical Libraries for .NET Professional

The VectorExtensions type exposes the following members.

Methods

  NameDescription
Public methodStatic memberApplyHodrickPrescottFilter
Applies Hodrick-Prescott smoothing to the vector.
Public methodStatic memberBoxCoxTransform
Returns the Box-Cox transform of the vector for the specified parameter.
Public methodStatic memberChange
Returns a vector whose observations are the difference between each observation and a previous observation.
Public methodStatic memberExponentialMovingAverage(VectorDouble, Double)
Returns a vector whose observations are the exponential moving average of the observations of the vector.
Public methodStatic memberExponentialMovingAverage(VectorDouble, Int32)
Returns a vector whose observations are the exponential moving average of the observations of the vector.
Public methodStatic memberExponentialMovingAverage(VectorDouble, Int32, Int32)
Returns a vector whose observations are the exponential moving average of the observations of the vector.
Public methodStatic memberExtrapolatedChange
Returns a vector whose observations are the extrapolated change of the observations over the specified lag.
Public methodStatic memberExtrapolatedGrowthRate
Returns a vector whose observations are the extrapolated exponential growth rate of the observations over the specified lag.
Public methodStatic memberExtrapolatedPercentChange
Returns a vector whose observations are the extrapolated percentage change of the observations over the specified lag.
Public methodStatic memberGrowthRate
Returns a vector whose observations are the exponential growth rate of the observations over the specified lag.
Public methodStatic memberLagT(VectorT)
Returns a vector whose observations are moved ahead by one observation.
Public methodStatic memberLagT(VectorT, Int32)
Returns a vector whose observations are moved ahead by the specified number of observations.
Public methodStatic memberLagT(VectorT, Int32, T)
Returns a vector whose observations are moved ahead by the specified number of observations.
Public methodStatic memberMovingAverage(VectorDouble, Int32)
Returns a vector whose observations are the simple moving average of the observations of the vector.
Public methodStatic memberMovingAverage(VectorDouble, Int32, Boolean)
Returns a vector whose observations are the simple moving average of the observations of the vector.
Public methodStatic memberMovingAverageAbsoluteDeviation
Returns a vector whose observations are the average absolute deviation of a range of observations from observations of another vector.
Public methodStatic memberMovingMaximum
Returns a vector whose observations are the maximum of a range of observations of the vector.
Public methodStatic memberMovingMinimum
Returns a vector whose observations are the minimum of a range of observations of the vector.
Public methodStatic memberMovingStandardDeviation
Returns a vector whose observations are the standard deviation of a range of observations of the vector.
Public methodStatic memberMovingSum
Returns a vector whose observations are the sum of a range of observations of the vector.
Public methodStatic memberPercentChange
Returns a vector whose observations are the percent change of the observations over the specified lag.
Public methodStatic memberPeriodToDateDifferences(VectorDouble, Int32, BoundaryIntervalBehavior, BoundaryIntervalBehavior)
Returns a vector whose observations are the difference between successive observations over intervals of observations.
Public methodStatic memberPeriodToDateDifferences(VectorDouble, VectorDateTime, VectorDateTime, BoundaryIntervalBehavior, BoundaryIntervalBehavior)
Returns a vector whose observations are the difference between successive observations over intervals of observations.
Public methodStatic memberPeriodToDateValues(VectorDouble, Int32, BoundaryIntervalBehavior, BoundaryIntervalBehavior)
Returns a vector whose observations are the cumulative sum over intervals of observations.
Public methodStatic memberPeriodToDateValues(VectorDouble, VectorDateTime, VectorDateTime, BoundaryIntervalBehavior, BoundaryIntervalBehavior)
Returns a vector whose observations are the cumulative sum over intervals of observations.
Public methodStatic memberPositiveToNegativeIndex
Returns a vector that represents an index comparing positive to negative values in the specified period..
Public methodStatic memberPositiveToNegativeRatio
Returns a vector that represents the ratio of positive to negative values in the specified period..
Public methodStatic memberQuantileT
Gets the specified quantile.
Public methodStatic memberQuantilesT
Gets the specified quantile.
Public methodStatic memberReferenceIndex(VectorDouble, Int32, Double)
Returns a vector that represents an index value relative to the specified base value.
Public methodStatic memberReferenceIndex(VectorDouble, Int32, Int32, Double)
Returns a vector that represents an index value relative to the specified range of base value.
Public methodStatic memberUseBackwardDifferenceEncoding
Specifies that backward difference encoding should be used when creating indicator variables.
Public methodStatic memberUseDeviationEncoding
Specifies that deviance encoding should be used when creating indicator variables.
Public methodStatic memberUseDummyEncoding
Specifies that dummy encoding (also called treatment encoding) should be used when creating indicator variables.
Public methodStatic memberUseForwardDifferenceEncoding
Specifies that forward difference encoding should be used when creating indicator variables.
Public methodStatic memberUseHelmertEncoding
Specifies that Helmert encoding should be used when creating indicator variables.
Public methodStatic memberUseInverseHelmertEncoding
Specifies that inverse Helmert encoding should be used when creating indicator variables.
Public methodStatic memberUsePolynomialEncoding
Specifies that orthogonal polynomial encoding should be used when creating indicator variables.
Public methodStatic memberUseSimpleEncoding
Specifies that simple encoding should be used when creating indicator variables.
Public methodStatic memberWeightedMovingAverage(VectorDouble, VectorDouble)
Returns a vector whose observations are the weighted moving average of the observations of the vector.
Public methodStatic memberWeightedMovingAverage(VectorDouble, Double)
Returns a vector whose observations are the weighted moving average of the observations of the vector.
Public methodStatic memberWeightedMovingAverage(VectorDouble, VectorDouble, Int32)
Returns a vector whose observations are the weighted moving average of the observations of the vector.
Public methodStatic memberWeightedMovingAverage(VectorDouble, Double, Int32)
Returns a vector whose observations are the weighted moving average of the observations of the vector.
Public methodStatic memberWeightedMovingAverage(VectorDouble, Int32, VectorDouble)
Returns a vector whose observations are the weighted moving average of the observations of the vector.
Top
See Also

Reference

VectorExtensions Class
Extreme.DataAnalysis Namespace

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