Results 61 to 70 of about 70,213 (199)
IEEE AccessUsing copulas in statistics evaluates the dependence between random variables. Copula modeling has significantly been used in many areas, especially in the search for multivariate distributions.
Amir Shahirinia +4 more
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Nonparametric Conditional Copula Density Estimation With Applications to the Body Mass Index
Stat, Volume 15, Issue 4, December 2026.ABSTRACT This study develops a nonparametric conditional copula density estimator that features a parametric carrier copula refined by an exponential series adjustment. We adopt the local likelihood approach for conditional distribution estimation and incorporate the influence of covariates via kernel smoothing.
Michael Z. Wu, Lan Zhou
wiley +1 more source
Mathematical and Computational ApplicationsThe increasing global reliance on wind and solar energy underscores the critical vulnerability of renewable systems to extreme weather, which can severely disrupt power generation.
Maashele Kholofelo Metwane +2 more
doaj +1 more source
IET Generation, Transmission & Distribution, 2020 This work focuses on calculating the amount of control reserve, which can be provided by a pool of renewable power plants on the next day. The power forecast of wind and solar power plants depends on the weather forecast, which always contains errors.
Stefan Möws +2 more
doaj +1 more source
Complex Versus Parsimonious Site‐Based Stochastic Ground Motion Models: Which One Is Better?
Earthquake Engineering &Structural Dynamics, Volume 55, Issue 14, Page 3714-3731, November 2026.ABSTRACT Stochastic ground motion models (GMMs) provide a probabilistic representation of seismic input and are increasingly important for uncertainty quantification (UQ) in earthquake engineering. This study focuses on site‐based stochastic GMMs, which learn the statistical features of selected datasets of seismic records and generate statistically ...
Maijia Su +2 more
wiley +1 more source
Model distances for vine copulas in high dimensions [PDF]
Statistics and Computing, 2017 Vine copulas are a flexible class of dependence models consisting of bivariate building blocks and have proven to be particularly useful in high dimensions. Classical model distance measures require multivariate integration and thus suffer from the curse of dimensionality.
Matthias Killiches +2 more
openaire +4 more sources
Austral Entomology, Volume 65, Issue 4, November 2026.ABSTRACT The Australian species of the Phasmida genus Anchiale Stål, 1875 (Phasmatinae: Phasmatini) are updated to include five species: Anchiale albopunctata (Kirby, 1896) stat. rev. (removed from synonymy with A. briareus (Gray, 1834)); A. briareus Gray, 1834 (= Ctenomorpha tessulata Gray, 1835 syn. nov.; = A. austrotessulata Brock & Hasenpush, 2007,
Braxton R. Jones +4 more
wiley +1 more source
An Econometric Study of Vine Copulas. [PDF]
We present a new recursive algorithm to construct vine copulas based on an underlying tree structure. This new structure is interesting to compute multivariate distributions for dependent random variables.
Dominique Guegan, Pierre-André Maugis
core +1 more source
Engineering Reports, Volume 8, Issue 10, October 2026.The paper consists of four parts. Specially, the first part analyzes the wind challenges of large‐span bridges, including the formation mechanism of wind‐induced vibration disaster of large‐span bridges and typical cases, as well as the limitations of the current wind design codes. The second part reviews the analysis models and experimental techniques
Sai Gong +4 more
wiley +1 more source
Stepwise Variational Inference with Vine Copulas
CoRRWe propose stepwise variational inference (VI) with vine copulas: a universal VI procedure that combines vine copulas with a novel stepwise estimation procedure of the variational parameters. Vine copulas consist of a nested sequence of trees built from copulas, where more complex latent dependence can be modeled with increasing number of trees.
Elisabeth Griesbauer +4 more
openaire +3 more sources