https://github.com/socr/tciu
Data Science, Time Complexity and Inferential Uncertainty (TCIU)
https://github.com/socr/tciu
Last synced: 8 months ago
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Data Science, Time Complexity and Inferential Uncertainty (TCIU)
- Host: GitHub
- URL: https://github.com/socr/tciu
- Owner: SOCR
- Created: 2019-05-27T19:33:38.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2023-02-27T20:27:26.000Z (over 3 years ago)
- Last Synced: 2025-10-11T11:51:40.004Z (8 months ago)
- Language: R
- Size: 78.5 MB
- Stars: 11
- Watchers: 1
- Forks: 6
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
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README
# TCIU
**Data Science, Time Complexity and Inferential Uncertainty (TCIU)**
Table of contents
=================
* [Table of contents](#table-of-contents)
* [Overview](#overview)
* [R Code](#r-code)
* [Python Code](#python-code)
* [Team](#team)
* [Acknowledgments](#acknowledgments)
* [References](#references)
Overview
========
The [SOCR Data Science Fundamentals project explores new theoretical representation and analytical strategies to understand large and complex data, time complexity and inferential uncertainty](http://www.socr.umich.edu/TCIU/). It utilizes information measures, entropy KL divergence, PDEs, Dirac’s bra-ket operators (〈 , 〉). This fundamentals of data science research project will explore time-complexity and inferential uncertainty in modeling, analysis and interpretation of large, heterogeneous, multi-source, multi-scale, incomplete, incongruent, and longitudinal data.
R Code
======
The examples, demonstrations and simulations are designed, built, implemented and validated in the [R environment](https://www.r-project.org).
The source R code for the package is in the [package (TCIU) folder](https://github.com/SOCR/TCIU/tree/master/package).
The source RMarkdown code for the website is in the [website folder](https://github.com/SOCR/TCIU/tree/master/website).
To interactively run of the demo code, following a [TCIU package installation](https://github.com/SOCR/TCIU/tree/master/package/TCIU), use the following command in the R console/shell:
```{r}
library("TCIU")
demo(fmri_demo_func, package="TCIU")
```
Python Code
===========
An early (pilot) version of a Python implementaiton of the TCIU package will be available in the [package (TCIU_python) folder](https://github.com/SOCR/TCIU/tree/master/package/TCIU_python). This is still under development and valudation ...
Team
====
[SOCR Team](http://www.socr.umich.edu/people/) including [Ivo D. Dinov](https://umich.edu/~dinov), [Milen V. Velev](https://www.socr.umich.edu/people/Milen_Velev.html), [Yongkai Qiu](https://www.socr.umich.edu/people/Yongkai_Qiu.html), [Zhe Yin](https://www.socr.umich.edu/people/Zhe_Yin.html), Yufei Yang, Yunjie Guo, Yupeng Zhang, Rongqian Zhang, Yuyao Liu, Jinwen Cao, Zijing Li, Daxuan Deng, [Yueyang Shen](https://www.socr.umich.edu/people/SOCR_Personnel_Yueyang.html), and others.
Acknowledgments
===============
This work is supported in part by NIH grants [P20 NR015331](www.socr.umich.edu/CSCD), [UL1TR002240](https://projectreporter.nih.gov/project_info_description.cfm?aid=9491961&icde=39078316), [P30 DK089503](http://mmoc.med.umich.edu/), [UL1TR002240](https://www.michr.umich.edu), and NSF grants [1916425](http://midas.umich.edu/), [1734853](http://brain-life.org/), [1636840](http://neurosciencenetwork.org/), [1416953](http://distributome.org), [0716055](http://socr.umich.edu) and [1023115](http://distributome.org). Students, trainees, scholars, and researchers from SOCR, BDDS, MNORC, MIDAS, MADC, MICHR, and the broad R-statistical computing community have contributed ideas, code, and support.
References
==========
* Dinov, ID and Velev, MV (2021) [Data Science: Time Complexity, Inferential Uncertainty, and Spacekime Analytics](https://www.degruyter.com/view/title/576646), De Gruyter STEM Series, Berlin/Boston, ISBN 9783110697803 / 3110697807.
* Wang, Y, Shen Y, Deng, D, Dinov, ID. (2022) [Determinism, Well-posedness, and Applications of the Ultrahyperbolic Wave Equation in Spacekime](https://doi.org/10.1016/j.padiff.2022.100280), Journal of Partial Differential Equations in Applied Mathematics, DOI: [10.1016/j.padiff.2022.100280](https://doi.org/10.1016/j.padiff.2022.100280), in press.
* Zhang, R, Zhang, Y, Liu, Y, Guo, Y, Shen, Y, Deng, D, Qiu, Y, Dinov, ID. (2022) [Kimesurface Representation and Tensor Linear Modeling of Longitudinal Data](https://doi.org/10.1007/s00521-021-06789-8), Neural Computing and Applications Journal, DOI: 10.1007/s00521-021-06789-8, in press.
* [TCIU Website](https://tciu.predictive.space/).
* [Spacekime](https://Spacekime.org).
* [TSPlotly package on CRAN](https://cran.r-project.org/web/packages/TSplotly/index.html).
* [TCIU package on CRAN](https://cran.r-project.org/web/packages/TCIU/).