Data Smoothing Commands - Maple Programming Help

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Data Smoothing Commands

  

The Statistics package provides various data smoothing functions. The following is a list of available commands.

  

 

ExponentialSmoothing

apply exponential smoothing to a data set

LinearFilter

apply linear filter to a data set

MovingAverage

compute moving averages for a data set

MovingMedian

compute moving medians for a data set

MovingStatistic

compute moving statistics for a data set

WeightedMovingAverage

compute weighted moving averages for a data set

  

The TimeSeriesAnalysis[ExponentialSmoothingModel] command also provides a form of smoothing.

Examples

Create 100 points on the curve y=sinπx10 and add some random noise.

withStatistics:

USampleNormal0,0.3,100

U:= 1 .. 100 VectorrowData Type: float8Storage: rectangularOrder: Fortran_order

(1)

Vseqsinπi10+Ui,i=1..100:

PPointPlotV:

Qplotsinπx10,x=0..100,thickness=3:

plots[display]P,Q

Compute 5-element moving averages.

WMovingAverageV,5

W:= 1 .. 96 VectorcolumnData Type: float8Storage: rectangularOrder: Fortran_order

(2)

RLineChartW,xcoords=seqi,i=2..98,thickness=3:

plots[display]P,Q,R

Apply exponential smoothing.

U1ExponentialSmoothingV,0.2

U1:= 1 .. 100 VectorcolumnData Type: float8Storage: rectangularOrder: Fortran_order

(3)

U2ExponentialSmoothingV,0.8

U2:= 1 .. 100 VectorcolumnData Type: float8Storage: rectangularOrder: Fortran_order

(4)

RLineChartU1,U2,color=red,blue,thickness=3:

plots[display]P,R

Use lowess smoothing.

Xseqi,i=1..100:

RScatterPlotX,V,lowess,degree=3,color=blue,thickness=3:

plots[display]P,Q,R

See Also

Statistics

Statistics[Commands]

Statistics[DataManipulation]

TimeSeriesAnalysis

TimeSeriesAnalysis[ExponentialSmoothingModel]

 


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