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Provide the core functionality to transform longitudinal data to complex-time (kime) data using analytic and numerical techniques, visualize the original time-series and reconstructed kime-surfaces, perform model based (e.g., tensor-linear regression) and model-free classification and clustering methods in the book Dinov, ID and Velev, MV. (2021) "Data Science: Time Complexity, Inferential Uncertainty, and Spacekime Analytics", De Gruyter STEM Series, ISBN 978-3-11-069780-3. <https://www.degruyter.com/view/title/576646>. The package includes 18 core functions which can be separated into three groups. 1) draw longitudinal data, such as Functional magnetic resonance imaging(fMRI) time-series, and forecast or transform the time-series data. 2) simulate real-valued time-series data, e.g., fMRI time-courses, detect the activated areas, report the corresponding p-values, and visualize the p-values in the 3D brain space. 3) Laplace transform and kimesurface reconstructions of the fMRI data.
Version: | 1.2.6 |
Depends: | R (≥ 3.5.0) |
Imports: | stats, ggplot2, dplyr, tidyr, RColorBrewer, fancycut, scales, plotly, gridExtra, ggpubr, ICSNP, rrcov, geometry, DT, forecast, fmri, pracma, zoo, extraDistr, parallel, foreach, spatstat.explore, spatstat.geom, cubature, doParallel, reshape2, MultiwayRegression, interp |
Suggests: | oro.nifti, magrittr, knitr, rmarkdown |
Published: | 2024-05-17 |
DOI: | 10.32614/CRAN.package.TCIU |
Author: | Yongkai Qiu [aut], Zhe Yin [aut], Jinwen Cao [aut], Yupeng Zhang [aut], Yuyao Liu [aut], Rongqian Zhang [aut], Yueyang Shen [aut, cre], Rouben Rostamian [ctb], Ranjan Maitra [ctb], Daniel Rowe [ctb], Daniel Adrian [ctb] (gLRT method for complex-valued fMRI statistics), Yunjie Guo [aut], Ivo Dinov [aut] |
Maintainer: | Yueyang Shen <petersyy at umich.edu> |
BugReports: | https://github.com/SOCR/TCIU/issues |
License: | GPL-3 |
URL: | https://github.com/SOCR/TCIU, https://www.socr.umich.edu/spacekime/, https://www.socr.umich.edu/TCIU/ |
NeedsCompilation: | yes |
SystemRequirements: | GNU make |
CRAN checks: | TCIU results |
Reference manual: | TCIU.pdf |
Vignettes: |
Laplace Transform and Kimesurface Transform of TCIU Analytics Workflow of TCIU Analytics |
Package source: | TCIU_1.2.6.tar.gz |
Windows binaries: | r-devel: TCIU_1.2.6.zip, r-release: TCIU_1.2.6.zip, r-oldrel: TCIU_1.2.6.zip |
macOS binaries: | r-release (arm64): TCIU_1.2.6.tgz, r-oldrel (arm64): TCIU_1.2.6.tgz, r-release (x86_64): TCIU_1.2.6.tgz, r-oldrel (x86_64): TCIU_1.2.6.tgz |
Old sources: | TCIU archive |
Please use the canonical form https://CRAN.R-project.org/package=TCIU to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.