Package: logitFD 1.0

Manuel Escabias

logitFD: Functional Principal Components Logistic Regression

Functions for fitting a functional principal components logit regression model in four different situations: ordinary and filtered functional principal components of functional predictors, included in the model according to their variability explanation power, and according to their prediction ability by stepwise methods. The proposed methods were developed in Escabias et al (2004) <doi:10.1080/10485250310001624738> and Escabias et al (2005) <doi:10.1016/j.csda.2005.03.011>.

Authors:Carmen Lucia Reina <[email protected]> Ana Maria Aguilera <[email protected]> and Manuel Escabias <[email protected]>

logitFD_1.0.tar.gz
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logitFD_1.0.tgz(r-4.4-emscripten)logitFD_1.0.tgz(r-4.3-emscripten)
logitFD.pdf |logitFD.html✨
logitFD/json (API)

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4 exports 0.00 score 58 dependencies 2 scripts 135 downloads

Last updated 3 years agofrom:7f5b170711. Checks:OK: 2. Indexed: yes.

Exports:logitFD.fpclogitFD.fpc.steplogitFD.pclogitFD.pc.step

Dependencies:ashbitopscliclustercodetoolscolorspacedeSolvedoParallelexpmfansifarverfdafda.uscfdsFNNforeachggplot2gluegtablehdrcdeisobanditeratorskernlabKernSmoothkskSampleslabelinglatticelifecyclelocfitmagrittrMASSMatrixmclustmgcvmulticoolmunsellmvtnormnlmepcaPPpillarpkgconfigplyrpracmapROCR6rainbowRColorBrewerRcppRCurlrlangscalesSuppDiststibbleutf8vctrsviridisLitewithr