Uncertainty Analysis With High Dimensional Dependence Modelling

By Collin Carbno. Technometrics, 2007

440 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/a356719b1ad5ffc0d1af198180d8b5f0e10501ec

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In Statistics and Probability

Citations in the corpus

Stochastic Modeling of Power Demand Due to EVs Using Copula (2012, methodology): “The rank correlation measures a monotonic relationship between variables [20], [21].”
Bayesian inference for multivariate copulas using pair-copula constructions. (2010, background): “The book by Kurowicka and Cooke (2006) discusses these vine constructions in detail but restricts the statistical inference to the case of Gaussian vines.”
Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine (2013, methodology): “To classify them Bedford and Cooke (2001, 2002) introduced the graphical model called vine , which is also treated in detail in Kurowicka and Cooke (2006) and Kurowicka and Joe (2011).”
Pair-copula constructions of multiple dependence (2009, methodology): “Our proposal extends the method of maximum pseudo-likelihood originally proposed for copulae by Oakes (1994), and later shown to be asymptotically normal and consistent both by Genest et al.”
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).”
SHAPLEY EFFECTS FOR SENSITIVITY ANALYSIS WITH CORRELATED INPUTS: COMPARISONS WITH SOBOL' INDICES, NUMERICAL ESTIMATION AND APPLICATIONS (2017, neutral): “However, in many applications, it is common that the input variables have a statistical dependence structure imposed by a probabilistic dependence function [6] (e.”
A Review on Global Sensitivity Analysis Methods (2014, positive): “Cobweb plots (Kurowicka and Cooke [48]), also called parallel coordinate plots, can be used to visualize the simulations as a set of trajectories.”
On a class of circulas: copulas for circular distributions (2015, background): “As in the linear case, the value of direct multivariate extensions of the circula is not especially clear, given the attraction of pair copula constructions (Bedford and Cooke 2002; Kurowicka and Cooke 2006; Aas et al. 2009) to more meaningfully model highly multivariate situations.”
Parameter estimation for pair-copula constructions (2013, background): “Accordingly, a number of hierarchical, copula-based structures have been proposed, among those the pair-copula construction (PCC) of Joe [22], further studied and considered by Bedford and Cooke [2, 3], Kurowicka and Cooke [30] and Aas et al.”
Probabilistic modeling of flood characterizations with parametric and minimum information pair-copula model (2016, methodology): “We briefly introduce these two vines and how they can be used to model multivariate data by a simple example (further details can be found in Aas et al., 2009; Kurowicka and Cooke, 2006).”
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].”
Extreme value properties of multivariate t copulas (2009, positive): “Based on partial correlations (see, e.g., Kurowicka and Cooke, 2006), for elliptical copulas that include t copulas, the correlation coefficients ρik, 1 ≤ i < k ≤ d, satisfy −1 ≤ ρik;j ≤ 1 or ρijρjk − √ (1 − ρ2ij)(1 − ρ2jk) ≤ ρik ≤ ρijρjk + √ (1 − ρ2ij)(1 − ρ2jk) , i < j < k. (1.3) Inequalities for…”
Pair‐copula constructions for non‐Gaussian DAG models (2012, methodology): “The basic idea of applying PCCs to distributions with certain conditional independence properties goes back to Hanea, Kurowicka, & Cooke (2006) and Kurowicka & Cooke (2006).”
Pair-Copula Constructions for Financial Applications: A Review (2016, methodology): “The notion of regular vines (R-vines) was introduced by Bedford and Cooke [8], and described in more detail in [9].”
Selecting and estimating regular vine copulae and application to financial returns (2012, methodology): “The following summarizes some deﬁnitions and results from Bedford and Cooke (2001), Bedford and Cooke (2002, Part 4) and Kurowicka and Cooke (2006, Chapter 4.4), where a tree is a graph in which each two nodes are connected by a unique sequence of edges.”
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).”
Selection strategies for regular vine copulae (2013, methodology): “First estimation procedures assuming the tree structure and the pair copula families to be known were developed in [Kurowicka and Cooke, 2008], while standard maximum likelihood (ML) inference for D-vines was studied in [Aas et al., 2009].”
Sequential Bayesian Model Selection of Regular Vine Copulas (2015, methodology): “This property makes copulas a very convenient tool to be used by statistical modelers (Nelsen (2006); McNeil et al. (2005); Kurowicka and Cooke (2006); Kurowicka and Joe (2010)).”