Results 81 to 90 of about 7,683 (263)
Copula–entropy theory for multivariate stochastic modeling in water engineering
Geoscience Letters, 2018 The copula–entropy theory combines the entropy theory and the copula theory. The entropy theory has been extensively applied to derive the most probable univariate distribution subject to specified constraints by applying the principle of maximum entropy.
Vijay P. Singh, Lan Zhang
doaj +1 more source
International Journal of Climatology, EarlyView.During the period 1901–2024, the dominant proportion of compound dry‐warm extremes in annual, June–July–August (JJA), and December–January–February (DJF) occurrences was the highest among the four types of compound precipitation and temperature extremes across global land areas, accounting for 40.1%, 50.3%, and 28.0%, respectively.
Ruting Yang +6 more
wiley +1 more source
Spatial and Temporal Patterns of Extreme Hourly Rainfall in the Hawaiian Islands
International Journal of Climatology, EarlyView.The extreme rainfall trends in Hawaiʻi were revealed by hourly rainfall data: Across islands, Kauaʻi and Hawaiʻi Island had larger events at a return period. Annual maximum series of 15 gauges showed significant positive trends. While extreme rainfall trends show increases or decreases regionally, the trends varied with rainfall duration.
Maxime Gayte +5 more
wiley +1 more source
Mathematical Methods in the Applied Sciences, EarlyView.We develop a full randomization of the classical hyper‐logistic growth model by obtaining closed‐form expressions for relevant quantities of interest, such as the first probability density function of its solution, the time until a given fixed population is reached, and the population at the inflection point.
Juan Carlos Cortés +2 more
wiley +1 more source
Bivariate postprocessing of wind vectors
Quarterly Journal of the Royal Meteorological Society, EarlyView.We introduce three novel bivariate postprocessing approaches and analyze their performance for joint postprocessing of bivariate wind‐vector components in Germany. Bivariate vine‐copula‐based models, a bivariate gradient‐boosted version of ensemble model output statistics (EMOS), and a bivariate distributional regression network (DRN) are compared with
Ferdinand Buchner +3 more
wiley +1 more source
Statistical post‐processing of operational dual‐resolution wind‐speed ensemble forecasts
Quarterly Journal of the Royal Meteorological Society, EarlyView.The performance of raw and post‐processed 50‐member medium‐ and 100‐member extended‐range 10‐m wind‐speed forecasts of the European Centre for Medium‐Range Weather Forecasts and their various dual‐resolution combinations is investigated. Results show that post‐processing improves skill and reduces the differences between the various configurations ...
Sándor Baran, Mária Lakatos
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High‐Dimensional Cumulative Sum Control Charts for Industrial Measurement Systems
Quality and Reliability Engineering International, EarlyView.ABSTRACT High dimensional sensing in modern factories and energy assets produces thousands of correlated signals. Detecting small process shifts is challenging because many classical multivariate charts lose power or become unstable. We present two cumulative sum procedures for two sample monitoring that remain effective when the number of variables is
Osama Alhadi +3 more
wiley +1 more source
Design flood estimation of cascade reservoirs based on vine-copula flood regional composition
Journal of Hydrology: Regional StudiesStudy region: The study region is the Yalong River basin, the largest tributary of the Jinsha River in China. Study focus: The most likely flood regional composition (MLFRC) method has been widely used to estimate the design flood of cascade reservoirs ...
Sirui Zhong +4 more
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Integrating Entropy and Copula Theories for Hydrologic Modeling and Analysis
Entropy, 2015 Entropy is a measure of uncertainty and has been commonly used for various applications, including probability inferences in hydrology. Copula has been widely used for constructing joint distributions to model the dependence structure of multivariate ...
Zengchao Hao, Vijay P. Singh
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Not All Missing Data are Equal: Choosing the Right Imputation Method for Binary Datasets
Quality and Reliability Engineering International, EarlyView.ABSTRACT Missing binary predictors are common in reliability, quality control, and industrial decision systems, yet imputation methods are often chosen by convenience rather than evidence. We conduct a Monte Carlo study comparing mode substitution, sequential hot‐deck, missForest, MICE, and KNN with three neighbourhood sizes under MCAR, MAR, and MNAR ...
Manuel Delfino, Fabio Rapallo
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