The hierarchical Bayesian quantile regression model was developed in the R Foundation for Statistical Computing Platform Desktop System Type x64-based PC with Intel(R) Core(TM) i7-9700 CPU 3.00 GHz 8 Cores 8 Logical Processors 64.0 GB RAM (64-bit) R version 4.2.0.
Correspondence: Department of Biological and Environmental Engineering, Cornell University, Ithaca 14853, NY, United States, nn289@cornell.edu
If you use the hierarchical Bayesian quantile regression model script (as a whole, or partially, and/or as a template for your research work), please cite the reference(s) below.
Najibi, N., Mukhopadhyay, S., & Steinschneider, S. (2022). Precipitation Scaling With Temperature in the Northeast US: Variations by Weather Regime, Season, and Precipitation Intensity. Geophysical Research Letters, 49(8), e2021GL097100.
@article{najibi2022precipitation,
title={Precipitation Scaling With Temperature in the Northeast US: Variations by Weather Regime, Season, and Precipitation Intensity},
author={Najibi, Nasser and Mukhopadhyay, Sudarshana and Steinschneider, Scott},
journal={Geophysical Research Letters},
volume={49},
number={8},
pages={e2021GL097100},
year={2022},
publisher={Wiley Online Library}
}Version 1.0 August 2021
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This project is licensed under the MIT License - see the LICENSE.md file for details.
Disclaimer: You are running the scripts/functions that means you will not blame the author(s)/developer(s) if they break your stuff. The scripts/functions are provided AS IS without warranty of any kind. Author(s) disclaim all implied warranties including, without limitation, any implied warranties of merchantability or of fitness for a particular purpose. In no event shall author(s) be held liable for any damages whatsoever (including, without limitation, any sorts of damages or loss) arising out of the use of or inability to use the scripts or documentations. Author(s) retain the right to alter this disclaimer at any time. The contents contained in this repository or within the articles are not the opinions of the funding agencies, affiliated university, or the U.S. Government but reflect the authors' opinions.
