Package: cfda 0.12.0

Quentin Grimonprez

cfda: Categorical Functional Data Analysis

Package for the analysis of categorical functional data. The main purpose is to compute an encoding (real functional variable) for each state <doi:10.3390/math9233074>. It also provides functions to perform basic statistical analysis on categorical functional data.

Authors:Cristian Preda [aut], Quentin Grimonprez [aut, cre], Vincent Vandewalle [ctb]

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cfda.pdf |cfda.html✨
cfda/json (API)
NEWS

# Install 'cfda' in R:

install.packages('cfda', repos = c('https://modal-inria.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/modal-inria/cfda/issues

Datasets:

biofam2 - Family life states from the Swiss Household Panel biographical survey
care - Care trajectories
flours - Flours dataset

On CRAN:

categorical-data functional-data-analysis hacktoberfest

4.18 score 3 stars 3 scripts 330 downloads 21 exports 62 dependencies

Last updated 10 hours agofrom:8ffc32257a. Checks:OK: 7. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 22 2024
R-4.5-win	OK	Nov 22 2024
R-4.5-linux	OK	Nov 22 2024
R-4.4-win	OK	Nov 22 2024
R-4.4-mac	OK	Nov 22 2024
R-4.3-win	OK	Nov 22 2024
R-4.3-mac	OK	Nov 22 2024

Exports:compute_duration compute_number_jumps compute_optimal_encoding compute_time_spent convertToCfd cut_data estimate_Markov estimate_pt generate_2State generate_Markov get_encoding get_state matrixToCfd plotComponent plotData plotEigenvalues plotIndicatorsReconstruction reconstructIndicators remove_duplicated_states statetable summary_cfd

Dependencies:ash bitops cli cluster colorspace cpp11 deSolve diagram dplyr expm fansi farver fda fds FNN generics ggplot2 glue gtable hdrcde isoband kernlab KernSmooth ks labeling lattice lifecycle locfit magrittr MASS Matrix mclust mgcv msm multicool munsell mvtnorm nlme pbapply pcaPP pillar pkgconfig pracma purrr R6 rainbow RColorBrewer Rcpp RCurl rlang scales shape stringi stringr survival tibble tidyr tidyselect utf8 vctrs viridisLite withr

Categorical Functional Data Analysis

Cristian Preda, Quentin Grimonprez

Rendered fromcfda.Rmdusingknitr::rmarkdownon Nov 22 2024.

Last update: 2024-11-22
Started: 2019-11-05

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Family life states from the Swiss Household Panel biographical survey	biofam2
Boxplot of time spent in each state	boxplot.timeSpent
Care trajectories	care
Compute duration of individuals	compute_duration
Compute the number of jumps	compute_number_jumps
Compute the optimal encoding for each state	compute_optimal_encoding
Compute time spent in each state	compute_time_spent
Convert data to categorical functional data	convertToCfd
Cut data to a maximal given time	cut_data
Estimate transition matrix and spent time	estimate_Markov
Estimate probabilities to be in each state	estimate_pt
Flours dataset	flours
Generate data following a 2 states model	generate_2State
Generate Markov Trajectories	generate_Markov
Extract the computed encoding	get_encoding
Extract the state of each individual at a given time	get_state
Plot the duration	hist.duration
Plot the number of jumps	hist.njump
Convert a matrix to a cfda data.frame	matrixToCfd
Plot the optimal encoding	plot.fmca
Plot the transition graph	plot.Markov
Plot probabilities	plot.pt
Plot Components	plotComponent
Plot categorical functional data	plotData
Plot Eigenvalues	plotEigenvalues
Plot reconstructed indicators	plotIndicatorsReconstruction
Predict the principal components for new trajectories	predict.fmca
Print a 'fmca' object	print.fmca
Reconstruct the indicators using encoding	reconstructIndicators
Remove duplicated states	remove_duplicated_states
Table of transitions	statetable
Summary	summary_cfd
Object Summaries	summary.fmca