Uncertainty Analysis with High Dimensional Dependence Modelling: Kurowicka/Uncertainty Analysis with High Dimensional Dependence Modelling

By Dorota Kurowicka, Roger M. Cooke. 2006

309 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/389e16c8e6b5c78cf0bbeea54718c78d5a14ae55

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In Artificial Intelligence

In Management Science and Operations Research

Citations in the corpus

Pair‐copula constructions for non‐Gaussian DAG models (2012, background): “The basic idea of applying PCCs to distributions with certain conditional independence properties goes back to Hanea, Kurowicka, & Cooke (2006) and Kurowicka & Cooke (2006).”
Bayesian model selection for D‐vine pair‐copula constructions (2011, methodology): “For a graphical representation of a d−dimensional D-vine we refer the reader to Kurowicka and Cooke (2006), Aas, Czado, Frigessi, and Bakken (2009) or Min and Czado (2010a).”
Expert Knowledge Elicitation: Subjective but Scientific (2019, background): “A review of this literature can be found in O’Hagan et al. (2006), while Kurowicka and Cooke (2006), O’Hagan (2012), European Food Safety Authority (2014), and Hanea et al. (2018) provide entry points to some more recent developments.”
Copula-Based Models of Systemic Risk in U.S. Agriculture: Implications for Crop Insurance and Reinsurance Contracts (2015, unknown): “Kurowicka and Cooke (2006) derived two special cases of vine copulas—the “canonical vine,” also known as the “C-vine,” and the “D-vine.””
Factor Copula Models for Replicated Spatial Data (2015, methodology): “Alternatively, one may use vine copula models, the joint distribution of which is constructed using bivariate, conditional linking copulas, including models with general structures, R-vines, and special cases such as C-vines; see Kurowicka and Cooke (2006) and Aas et al. (2009) for details.”
Pair Copula Constructions for Multivariate Discrete Data (2012, background): “Kurowicka and Cooke (2006) and Aas et al. (2009) were the first to exploit this decomposition to construct a statistical model where each bivariate building block follows some parametric copula.”
On Families of Distributions with Shape Parameters (2015, unknown): “This is well reﬂected in the copula literature where high-dimensional direct copulas are becoming largely eschewed in favour of pair-copula constructions (e.g. Bedford & Cooke, 2002, Kurowicka & Cooke, 2006, Aas, Czado, Frigessi & Bakken, 2009, Czado, 2010).”
A multivariate conditional model for streamflow prediction and spatial precipitation refinement (2015, methodology): “A MULTIVARIATE CONDITIONAL MODEL 10,117 modeling scheme of vine copulas is based on the decomposition of an n-dimensional multivariate density into n(n 1)/2 bivariate copula densities [Kurowicka and Cooke, 2006; Aas et al., 2009; Ren et al., 2014].”
Truncated regular vines in high dimensions with application to financial data (2012, methodology): “The PCC was originally proposed by Joe (1996) and has further been explored by Bedford & Cooke (2001, 2002) and Kurowicka & Cooke (2006).”
Models for construction of multivariate dependence – a comparison study (2009, background): “This structure was originally proposed by Joe (1996), and later discussed in detail by Bedford and Cooke (2001, 2002), Kurowicka and Cooke (2006) (simulation) and Aas et al. (2007) (inference).”
Copulas in Econometrics (2014, methodology): “Several methods have been proposed recently, including those for constructing higher-dimensional Archimedean copulas (see Hering et al. 2010, Hofert & Scherer 2011), and the pair-copula construction approach known as vines (see Kurowicka & Cooke 2006, Aas et al. 2009, Acar et al. 2012).”