Zobrazeno 1 - 10
of 356
pro vyhledávání: '"Naveau, Philippe"'
Accurate precipitation forecasts have a high socio-economic value due to their role in decision-making in various fields such as transport networks and farming. We propose a global statistical postprocessing method for grid-based precipitation ensemb
Externí odkaz:
http://arxiv.org/abs/2407.02125
Proper scoring rules are an essential tool to assess the predictive performance of probabilistic forecasts. However, propriety alone does not ensure an informative characterization of predictive performance and it is recommended to compare forecasts
Externí odkaz:
http://arxiv.org/abs/2407.00650
Causal asymmetry is based on the principle that an event is a cause only if its absence would not have been a cause. From there, uncovering causal effects becomes a matter of comparing a well-defined score in both directions. Motivated by studying ca
Externí odkaz:
http://arxiv.org/abs/2405.10371
Generating accurate extremes from an observational data set is crucial when seeking to estimate risks associated with the occurrence of future extremes which could be larger than those already observed. Applications range from the occurrence of natur
Externí odkaz:
http://arxiv.org/abs/2306.10987
In extreme value theory and other related risk analysis fields, probability weighted moments (PWM) have been frequently used to estimate the parameters of classical extreme value distributions. This method-of-moment technique can be applied when seco
Externí odkaz:
http://arxiv.org/abs/2306.10806
The statistical modeling of discrete extremes has received less attention than their continuous counterparts in the Extreme Value Theory (EVT) literature. One approach to the transition from continuous to discrete extremes is the modeling of threshol
Externí odkaz:
http://arxiv.org/abs/2210.15253
The theoretical advances on the properties of scoring rules over the past decades have broadened the use of scoring rules in probabilistic forecasting. In meteorological forecasting, statistical postprocessing techniques are essential to improve the
Externí odkaz:
http://arxiv.org/abs/2205.04360
Machine learning classification methods usually assume that all possible classes are sufficiently present within the training set. Due to their inherent rarities, extreme events are always under-represented and classifiers tailored for predicting ext
Externí odkaz:
http://arxiv.org/abs/2112.13738
Autor:
Buriticá, Gloria, Naveau, Philippe
Heavy rainfall distributional modeling is essential in any impact studies linked to the water cycle, e.g.\ flood risks. Still, statistical analyses that both take into account the temporal and multivariate nature of extreme rainfall are rare, and oft
Externí odkaz:
http://arxiv.org/abs/2112.02878
Autor:
Rivoire, Pauline, Gall, Philomène Le, Favre, Anne-Catherine, Naveau, Philippe, Martius, Olivia
Accurate estimation of daily rainfall return levels associated with large return periods is needed for a number of hydrological planning purposes, including protective infrastructure, dams, and retention basins. This is especially relevant at small s
Externí odkaz:
http://arxiv.org/abs/2112.02182