fda.classification
fda.classification This set of functions visualise Functional Data (data comming from functions) at a discrete time using R. The Detailed proposal is available on this blog
Install the development version using install_github within Hadley's devtools package.
install.packages("devtools")
require(devtools)
devtools::install_github("dapr12/fda.classification")
library('fda.classification')Note:
Windows users have to first install Rtools.
- [fda] (http://cran.r-project.org/web/packages/fda/index.html)
- [splines] (http://cran.r-project.org/web/packages/splines/index.html)
- [MASS] (http://cran.r-project.org/web/packages/MASS/index.html)
- [KernSmooth] (http://cran.r-project.org/web/packages/KernSmooth/index.html)
- [ks] (http://cran.r-project.org/web/packages/ks/index.html)
For examples
- [fdaExamples] (https://github.com/dapr12/fdaexamples/blob/master/fdaexamples.R)
fdaclass(mdata, argval, rangeval) outliergram(fdaobj)smoothfda(fdaobj , bandwidth, degree )gcsvc( fdaobj, norder, lambda, Lf, Intv )smoothbsplines( fdaobj, norder, lambda, Lf)fderiv(fdaobj,nderiv) Medianfd(Smoothfda)dpout(Eigenvalues, plotting)pcafd( fdaobj, nharm )densityScores(pcaobj2, 2)fdensity( fdaobj, pcaobj, bandwith, plotting)varfd(Smoothfda)classfd(Classlearn, train, test)pdfclasf(data, test, indClass0, indClass1, indtest )simulatefda( nsamples, ndrawn, rangeval, mean, sigma )