Citations and References
========================

Citation
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If you use **nsEVDx** in your research, please cite the following:

* Kafle, N., & Meier, C. I. (2025). *nsEVDx: A Python library for modeling Non-Stationary Extreme Value Distributions*. arXiv preprint `arXiv:2509.07261 <https://arxiv.org/abs/2509.07261>`_.
* Kafle, N., & Meier, C. (2025). *nsEVDx: A Python Library for Modeling Non-Stationary Extreme Value Distributions (v0.1.0)*. Zenodo. `https://doi.org/10.5281/zenodo.15850043 <https://doi.org/10.5281/zenodo.15850043>`_

References
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.. hlist::
   :columns: 1

   * Betancourt, M. (2017). *A Conceptual Introduction to Hamiltonian Monte Carlo*. arXiv: Methodology.
   * Coles, S. (2007). *An introduction to statistical modeling of extreme values* (4th. printing). Springer. `https://doi.org/10.1007/978-1-4471-3675-0 <https://doi.org/10.1007/978-1-4471-3675-0>`_
   * Gilleland, E. (2025). *extRemes: Extreme Value Analysis*. `https://doi.org/10.32614/CRAN.package.extRemes <https://doi.org/10.32614/CRAN.package.extRemes>`_
   * Heffernan J. E., Stephenson A.G., & Gilleland E. (2003). *Ismev: An Introduction to Statistical Modeling of Extreme Values*. `https://CRAN.R-project.org/package=ismev <https://CRAN.R-project.org/package=ismev>`_
   * Hosking, J. R. M., & Wallis, J. R. (1997). *Regional Frequency Analysis: An Approach Based on L-Moments* (Vol. 93). Cambridge University Press. `https://doi.org/10.1017/cbo9780511529443 <https://doi.org/10.1017/cbo9780511529443>`_
   * IRSN. (2024). *NSGEV: Non-Stationary GEV Time Series*. `https://github.com/IRSN/NSGEV/ <https://github.com/IRSN/NSGEV/>`_
   * Kafle, N., & Meier, C. (n.d.). *Detecting trends in short duration extreme precipitation over SEUS using neighborhood based method*. Manuscript in Preparation.
   * Kafle, N., & Meier, C. (2025). *Evaluating Methodologies for Detecting Trends in Short-Duration Extreme Rainfall in the Southeastern United States*. Extreme Hydrological or Critical Event Analysis-III, EWRI Congress 2025, Anchorage, AK, U.S. `https://alaska2025.eventscribe.net <https://alaska2025.eventscribe.net>`_
   * Kafle, N., Peleg, N., & Meier, C. I. *Detecting Spatially Consistent Trends in Sub-Hourly Extreme Rainfall Using a Neighborhood-Based Method*. AGU25.
   * Oriol Abril-Pla et al. (2023). *PyMC: A modern, and comprehensive probabilistic programming framework in Python*. PeerJ Computer Science, 9, e1516. `https://doi.org/10.7717/peerj-cs.1516 <https://doi.org/10.7717/peerj-cs.1516>`_
   * Paciorek, C. (2016). *climextRemes: Tools for Analyzing Climate Extremes*. `https://CRAN.R-project.org/package=climextRemes <https://CRAN.R-project.org/package=climextRemes>`_
   * Robert, C. P., & Casella, G. (2009). *Introducing Monte Carlo Methods with R*. `https://doi.org/10.1007/978-1-4419-1576-4 <https://doi.org/10.1007/978-1-4419-1576-4>`_
   * Roberts, G. O., & Tweedie, R. L. (1996). *Exponential Convergence of Langevin Distributions and Their Discrete Approximations*. Bernoulli, 2 (4), 341. `https://doi.org/10.2307/3318418 <https://doi.org/10.2307/3318418>`_
   * Stan development Team. (2023a). *CmdStan: The command-line interface to Stan*. `https://mc-stan.org/users/interfaces/cmdstan <https://mc-stan.org/users/interfaces/cmdstan>`_
   * Stan development Team. (2023b). *PyStan: The python interface to Stan*. `https://pystan.readthedocs.io/ <https://pystan.readthedocs.io/>`_