Articles | Volume 27, issue 15
https://doi.org/10.5194/hess-27-2935-2023
© Author(s) 2023. This work is distributed under the Creative Commons Attribution 4.0 License.
Research article
| 
09 Aug 2023
Research article |
| 09 Aug 2023
| 09 Aug 2023
Bayesian parameter inference in hydrological modelling using a Hamiltonian Monte Carlo approach with a stochastic rain model
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Cited articles
Ailliot, P., Allard, D., Monbet, V., and Naveau, P.: Stochastic weather
generators: An overview of weather type models, J. Soc. Fr. Stat., 156,
101–113, 2015. a
Albert, C., Künsch, H. R., and Scheidegger, A.: A Simulated Annealing
Approach to Approximate Bayes Computations, Stat. Comput., 25, 1217–1232,
https://doi.org/10.1007/s11222-014-9507-8, 2015. a
Andrieu, C., Doucet, A., and Holenstein, R.: Particle Markov chain Monte Carlo methods, J. Roy. Stat. Soc. B, 72, 269–342,
https://doi.org/10.1111/j.1467-9868.2009.00736.x, 2010. a
Bacci, M., Dal Molin, M., Fenicia, F., Reichert, P., and Šukys, J.:
Application of stochastic time dependent parameters to improve the
characterization of uncertainty in conceptual hydrological models, J. Hydrol., 612, 128057, https://doi.org/10.1016/j.jhydrol.2022.128057, 2022. a
