Minor changes in readme files

tee-lab · Sep 16, 2024 · 3361d17 · 3361d17
1 parent 0e139b4
commit 3361d17
Show file tree

Hide file tree

Showing 2 changed files with 3 additions and 5 deletions.
diff --git a/README.md b/README.md
@@ -136,7 +136,7 @@ For more information about PyDaddy, check out the [package documentation](https:
 ### Citation
 If you are using this package in your research, please cite the associated [paper](https://arxiv.org/abs/2205.02645) as follows:
 
-Nabeel, A., Karichannavar, A., Palathingal, S., Jhawar, J., Bruckner, B., Danny Raj, M., & Guttal, V., "Discovering stochastic dynamical equations from ecological time series data", arXiv preprint [arXiv:2205.02645](https://arxiv.org/abs/2205.02645), to appear in <strong>The American Naturalist</strong>. 
+Nabeel, A., Karichannavar, A., Palathingal, S., Jhawar, J., Brückner, B., Danny Raj, M., & Guttal, V., "Discovering stochastic dynamical equations from ecological time series data", arXiv preprint [arXiv:2205.02645](https://arxiv.org/abs/2205.02645), to appear in <strong>The American Naturalist</strong>. 
 
 ### Funding
 This study was partially funded by Science and Engineering Research Board, Department of Science and Technology, Government of India to Vishwesha Guttal. 

diff --git a/docs/source/citation.rst b/docs/source/citation.rst
@@ -1,8 +1,6 @@
 Citing PyDaddy
 ==============
 
-If you are using this package in your research, please cite the repository and the associated paper as follows:
+If you are using this package or any of the included code in your research, please cite the associated manuscript as follows:
 
-Nabeel, A., Karichannavar, A., Palathingal, S., Jhawar, J., Bruckner, D., Danny Raj, M., & Guttal, V. (2022). PyDaddy: A Python Package for Discovering SDEs from Time Series Data (Version 1.1.1) [Computer software]. https://github.com/tee-lab/PyDaddy
-
-Nabeel, A., Karichannavar, A., Palathingal, S., Jhawar, J., Bruckner, D., Danny Raj, M., & Guttal, V. (2022). PyDaddy: A Python package for discovering stochastic dynamical equations from timeseries data. arXiv preprint arXiv:2205.02645.
+Nabeel, A., Karichannavar, A., Palathingal, S., Jhawar, J., Brückner, D., Danny Raj, M., & Guttal, V. (2022). PyDaddy: A Python package for discovering stochastic dynamical equations from timeseries data. arXiv preprint arXiv:2205.02645.