knitr::opts_chunk$set(echo = TRUE) library(POIFD)
Software companion for the paper “Integrated Depth for Partially Observed Functiona Data” (Elías, Antonio, Jiménez, Raúl, Paganoni, Anna M. and Sangalli, Laura M., 2020).
It implements the proposed depth measures, functional boxplot and functional outliergram for partially observed functional data.
#install the package devtools::install_github("aefdz/POIFD") #load the package library(POIFD)
#Generate data sparse_gaussian <- gaussian_PoFD(n=10, p=200, type="sparse", observability=0.5) common_gaussian <- gaussian_PoFD(n=10, p=200, type="common", observability=0.5) interval_gaussian <- gaussian_PoFD(n=10, p=200, type="interval", ninterval=3, observability=0.5) #plot the data sets plot_sparse <- plot_PoFD(sparse_gaussian$pofd) plot_interval <- plot_PoFD(interval_gaussian$pofd) plot_common <- plot_PoFD(common_gaussian$pofd) plot_sparse plot_interval plot_common
mbd <- POIFD(common_gaussian$pofd, type = "MBD") (median <- mbd[1])
data(exampleData) fboxplot <- boxplot_PoFD(exampleData$PoFDextremes_outliers, centralRegion = 0.5, fmag = 1.5, fdom = 1) fboxplot$magnitude fboxplot$domain fboxplot$fboxplot
outliergram <- outliergram_PoFD(exampleData$PoFDextremes_outliers) outliergram$shape outliergram$outliergram
Elías, Antonio, Jiménez, Raúl, Paganoni, Anna M. and Sangalli, Laura M. (2020). Integrated Depths for Partially ObservedFunctional Data. (submitted)
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