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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: | 1.2.5 |
| 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 |
| Suggests: | oro.nifti, magrittr, knitr, rmarkdown |
| Published: | 2024-03-08 |
| Author: | Yongkai Qiu [aut, cre], Zhe Yin [aut], Jinwen Cao [aut], Yupeng Zhang [aut], Yuyao Liu [aut], Rongqian Zhang [aut], 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: | Yongkai Qiu <yongkai 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_1.2.5.tar.gz |
| Windows binaries: | r-devel: TCIU_1.2.5.zip, r-release: TCIU_1.2.5.zip, r-oldrel: TCIU_1.2.5.zip |
| macOS binaries: | r-release (arm64): TCIU_1.2.5.tgz, r-oldrel (arm64): TCIU_1.2.5.tgz, r-release (x86_64): TCIU_1.2.5.tgz, r-oldrel (x86_64): TCIU_1.2.5.tgz |
| Old sources: | TCIU archive |
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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.
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