| Field | Value |
|---|---|
| Title | PREDICTIVITY |
| Type | Source Code |
| Language | Python |
| License | |
| Status | Research Code |
| Update Frequency | NO |
| Date Published | 2021-04-27 |
| Date Updated | 2021-08-29 |
| Portal | https://github.com/tulip-lab/open-code |
| URL | https://github.com/tulip-lab/open-code/tree/master/PREDICTIVITY |
| Publisher | TULIP Lab |
| Point of Contact | A/Prof. Gang Li |
This package (PREDICTIVITY) is the algorithm for calculating tourism demand data predictivity. Please be aware that:
- The entropy calculation is depending on the distance value r.
- For very small distance value r, the predictivity will be unavailable.
If you use it for a scientific publication, please include a reference to this paper.
- Yishuo Zhang, Gang Li, Birgit Muskat, HuyQuan Vu, Rob Law (2021). Predictivity of tourism demand data. Annals of Tourism Research
BibTex information:
@article{ZLML2021,
title = {Predictivity of tourism demand data},
journal = {Annals of Tourism Research},
volume = {89},
pages = {103234},
year = {2021},
issn = {0160-7383},
doi = {https://doi.org/10.1016/j.annals.2021.103234},
url = {https://www.sciencedirect.com/science/article/pii/S0160738321001122},
author = {Yishuo Zhang and Gang Li and Birgit Muskat and Huy Quan Vu and Rob Law},
keywords = {Data characteristics, Entropy, Predictivity, Tourism demand forecasting}
}
- Python 3.6