Method ao/interpmissing


  INTERPMISSING interpolate missing samples in a time-series.
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  INTERPMISSING interpolate missing samples in a time-series. Missing samples
                are identified as being those where the time-span between one
                sample and the next is larger than d/fs where d is a
                tolerance value. Missing data is then placed in the gap in
                steps of 1/fs. Obviously this is only really correct for
                evenly sampled time-series.
 
  CALL:        bs = interpmissing(as)
 
  INPUTS:      as  - array of analysis objects
               pl  - parameter list (see below)
 
  OUTPUTS:     bs  - array of analysis objects, one for each input
 
 
  Parameters Description
 
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Method Details
Access public
Defining Class ao
Sealed 0
Static 0

Parameter Description

Default

no description
Key Default Value Options Description
D 1.5 none The time interval tolerance for finding missing samples.
METHOD 'spline'
  • 'nearest'
  • 'linear'
  • 'spline'
  • 'pchip'
  • 'v5cubic'
Specify the interpolation method. Choose between:
  • nearest - nearest neighbor interpolation
  • linear - linear interpolation
  • spline - piecewise cubic spline interpolation (SPLINE)
  • pchip - shape-preserving piecewise cubic interpolation
  • v5cubic - the cubic interpolation from MATLAB 5, which does not extrapolate and uses 'spline' if X is not equally spaced.
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Some information of the method ao/interpmissing are listed below:
Class name ao
Method name interpmissing
Category Signal Processing
Package name ltpda
VCS Version 3f8d61c792503a5b5ec8a0a153efb23b65da24a9
Min input args 1
Max input args -1
Min output args 1
Max output args -1




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