Stochastic simulation of non-stationary meteorological time-series daily precipitation indicators, maximum and minimum air temperature simulation using latent and transformed Gaussian processes › Research Explorer

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Stochastic simulation of non-stationary meteorological time-series daily precipitation indicators, maximum and minimum air temperature simulation using latent and transformed Gaussian processes

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Computational Mathematics Section

DOI

https://doi.org/10.5220/0006358801730179
Final published version

Nina Kargapolova

Original language	English
Title of host publication	SIMULTECH 2017 - Proceedings of the 7th International Conference on Simulation and Modeling Methodologies, Technologies and Applications
Editors	Floriano De Rango, Tuncer Oren, Mohammad S. Obaidat
Publisher	SciTePress
Pages	173-179
Number of pages	7
ISBN (Electronic)	9789897582653
ISBN (Print)	9789897582653
DOIs	https://doi.org/10.5220/0006358801730179
Publication status	Published - 1 Jan 2017
Event	7th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Madrid, Spain Duration: 26 Jul 2017 → 28 Jul 2017 Conference number: 7

Publication series

Name	SIMULTECH 2017 - Proceedings of the 7th International Conference on Simulation and Modeling Methodologies, Technologies and Applications

Conference

Conference	7th International Conference on Simulation and Modeling Methodologies, Technologies and Applications
Abbreviated title	SIMULTECH 2017
Country/Territory	Spain
City	Madrid
Period	26.07.2017 → 28.07.2017

Research areas

Air Temperature, Daily Precipitation, Extreme Weather Event, Non-stationary Random Process, Stochastic Simulation

ID: 9912947