TCIU
Spacekime Analytics, Time Complexity and Inferential Uncertainty
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.2.8 |
rolling linux/jammy R-4.5 | TCIU_1.2.8.tar.gz |
4.8 MiB |
1.2.8 |
rolling linux/noble R-4.5 | TCIU_1.2.8.tar.gz |
4.8 MiB |
1.2.8 |
rolling source/ R- | TCIU_1.2.8.tar.gz |
4.3 MiB |
1.2.8 |
latest linux/jammy R-4.5 | TCIU_1.2.8.tar.gz |
4.8 MiB |
1.2.8 |
latest linux/noble R-4.5 | TCIU_1.2.8.tar.gz |
4.8 MiB |
1.2.8 |
latest source/ R- | TCIU_1.2.8.tar.gz |
4.3 MiB |
1.2.8 |
2026-04-26 source/ R- | TCIU_1.2.8.tar.gz |
4.3 MiB |
1.2.8 |
2026-04-23 source/ R- | TCIU_1.2.8.tar.gz |
4.3 MiB |
1.2.8 |
2026-04-09 windows/windows R-4.5 | TCIU_1.2.8.zip |
4.8 MiB |
1.2.7 |
2025-04-20 source/ R- | TCIU_1.2.7.tar.gz |
4.2 MiB |