Feature Extraction for Discretely-Sampled Functional Data

Discretely-sampled function is first smoothed. Features of the smoothed function are then extracted. Some of the key features include mean value, first and second derivatives, critical points (i.e. local maxima and minima), curvature of cunction at critical points, wiggliness of the function, noise in data, and outliers in data.


News


features NEWS

Third version

o Released December 01, 2015.
o Added `...' in some of the calls to the smoothers so that smoothing options can be specified by the user
o changed the default `npts' from 100 to max(100, length(y))

Second version

o Released August 17, 2011.
o Added S3 methods for class "features"
o Two methods: plot (for plotting) and fget (for extracting features) 
o Removed the `plot.it' option

First version

o Released August 12, 2011.

Reference manual

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install.packages("features")

2015.12-1 by Ravi Varadhan, 4 years ago


http://www.jhsph.edu/agingandhealth/People/Faculty_personal_pages/Varadhan.html


Browse source code at https://github.com/cran/features


Authors: Ravi Varadhan , Johns Hopkins University , and MKG Subramaniam , AT&T Reserach Labs.


Documentation:   PDF Manual  


Task views: Numerical Mathematics


GPL (>= 2) license


Depends on lokern


See at CRAN