Results 71 to 80 of about 70,213 (199)
Explaining predictive models using Shapley values and non-parametric vine copulas
Dependence Modeling, 2021 In this paper the goal is to explain predictions from complex machine learning models. One method that has become very popular during the last few years is Shapley values.
Aas Kjersti +3 more
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Bayesian Model Selection of Regular Vine Copulas [PDF]
Bayesian Analysis, 2013 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gruber, Lutz F., Czado, Claudia
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Water Resources Research, Volume 62, Issue 9, September 2026.Abstract Pollution and deposition of sediments in rivers and streams are critical environmental, ecological, navigational, and recreational concerns. While several well‐known watershed models such as SWAT (Soil and Water Assessment Tool) and HSPF (Hydrological Simulation Program‐FORTRAN) are applied to predict sediment concentrations and loads in ...
Ying Ouyang
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Tail Risk in Weather Derivatives
CommoditiesWeather derivative markets, particularly Chicago Mercantile Exchange (CME) Heating Degree Day (HDD) and Cooling Degree Day (CDD) futures, face challenges from complex temperature dynamics and spatially heterogeneous co-extremes that standard Gaussian ...
Tuoyuan Cheng +2 more
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Vine Copulas as Differentiable Computational Graphs
CoRRVine copulas are sophisticated models for multivariate distributions and are increasingly used in machine learning. To facilitate their integration into modern ML pipelines, we introduce the vine computational graph, a DAG that abstracts the multilevel vine structure and associated computations.
Tuoyuan Cheng +3 more
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Predicting times to event based on vine copula models
Computational Statistics & Data Analysis, 2022 In statistics, time-to-event analysis methods traditionally focus on the estimation of hazards. In recent years, machine learning methods have been proposed to directly predict the event times. We propose a method based on vine copula models to make point and interval predictions for a right-censored response variable given mixed discrete-continuous ...
Shenyi Pan, Harry Joe
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Risk Measurement of Stock Markets in BRICS, G7, and G20: Vine Copulas versus Factor Copulas
, 2019 Multivariate copulas have been widely used to handle risk in the financial market. This paper aimed to adopt two novel multivariate copulas, Vine copulas and Factor copulas, to measure and compare the financial risks of the emerging economy, developed ...
Jianxu Liu +2 more
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Mixed D-vine copula-based conditional quantile model for stochastic monthly streamflow simulation
Water Science and EngineeringCopula functions have been widely used in stochastic simulation and prediction of streamflow. However, existing models are usually limited to single two-dimensional or three-dimensional copulas with the same bivariate block for all months.
Wen-zhuo Wang +5 more
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The Canadian Journal of Chemical Engineering, Volume 104, Issue 8, Page 4079-4100, August 2026.Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos +3 more
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Compound Impacts of Drought and Soil Salinity on Maize Productivity
Water Resources Research, Volume 62, Issue 8, August 2026.Abstract Intensifying soil drought poses a significant threat to maize yields in China. However, the compounding effects of soil drought and salinity remain poorly understood. Here, we analyze maize yield trends in China from 1982 to 2016 and show that an increase in the total number of drought days is associated with significant yield declines.
Huiying Li, Shuo Wang
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