Copula theory and probabilistic sensitivity analysis: is there a connection?
From MaRDI portal
Publication:1740560
DOI10.1016/j.ejor.2019.03.034zbMath1430.62103OpenAlexW2927131475WikidataQ128143572 ScholiaQ128143572MaRDI QIDQ1740560
Emanuele Borgonovo, Elmar Plischke
Publication date: 30 April 2019
Published in: European Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ejor.2019.03.034
Measures of association (correlation, canonical correlation, etc.) (62H20) Characterization and structure theory for multivariate probability distributions; copulas (62H05)
Related Items (6)
Estimation of high-order moment-independent importance measures for Shapley value analysis ⋮ Sensitivity Analysis Based on Cramér--von Mises Distance ⋮ Sensitivity measures based on scoring functions ⋮ Probabilistic sensitivity measures as information value ⋮ Analysis of Markov chain approximation for Asian options and occupation-time derivatives: Greeks and convergence rates ⋮ Nonparametric estimation of probabilistic sensitivity measures
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Greedy function approximation: A gradient boosting machine.
- Copula-based dependence measures
- Sensitivity analysis: a review of recent advances
- The contagion channels of July--August-2011 stock market crash: a DAG-copula based approach
- A note on the asymptotic behavior of the Bernstein estimator of the copula density
- Comparison, utility, and partition of dependence under absolutely continuous and singular distributions
- An introduction to copulas.
- Axiomatic characterizations of information measures
- Efficient risk simulations for linear asset portfolios in the \(t\)-copula model
- On nonparametric measures of dependence for random variables
- Generalized trapezoidal distributions
- Making best use of model evaluations to compute sensitivity indices
- Bézier and B-spline techniques
- Time-varying quantile association regression model with applications to financial contagion and VaR
- A global tolerance approach to sensitivity analysis in linear programming
- Vines -- a new graphical model for dependent random variables.
- Measuring the subprime crisis contagion: evidence of change point analysis of copula functions
- Gini's mean difference: a superior measure of variability for non-normal distributions
- Global sensitivity measures from given data
- Robust portfolio optimization with copulas
- Orderings of coherent systems with randomized dependent components
- The $f$-Sensitivity Index
- When Is a Model Good Enough? Deriving the Expected Value of Model Improvement via Specifying Internal Model Discrepancies
- Copula-Based Multivariate Input Models for Stochastic Simulation
- Multiattribute Utility Copulas
- Accounting for Parameter Uncertainty in Large-Scale Stochastic Simulations with Correlated Inputs
- Importance Sampling for Portfolio Credit Risk
- Correlations and Copulas for Decision and Risk Analysis
- Sensitivity Analysis Based on Cramér--von Mises Distance
- Dependence Modeling with Copulas
- Strong measures of concordance and convergence in probability
- On measures of dependence
- Multiattribute Utility Functions Satisfying Mutual Preferential Independence
- Relative Entropy Measures of Multivariate Dependence
- Rank Transformations as a Bridge Between Parametric and Nonparametric Statistics
- On the Relative Importance of Input Factors in Mathematical Models
- THE BERNSTEIN COPULA AND ITS APPLICATIONS TO MODELING AND APPROXIMATIONS OF MULTIVARIATE DISTRIBUTIONS
- Global Sensitivity Analysis
- A Copula‐Based Non‐parametric Measure of Regression Dependence
- Detecting Dependence With Kendall Plots
- Global sensitivity analysis with dependence measures
- Discrepancy Theory and Quasi-Monte Carlo Integration
- Utility Copula Functions Matching All Boundary Assessments
- On the Exact Region Determined by Kendall's τ and Spearman's ρ
- High-dimensional integration: The quasi-Monte Carlo way
- Distribution Free Tests of Independence Based on the Sample Distribution Function
- Copula Models for Aggregating Expert Opinions
- Transformations and Invariance in the Sensitivity Analysis of Computer Experiments
- A Non-Parametric Test of Independence
- On Information and Sufficiency
This page was built for publication: Copula theory and probabilistic sensitivity analysis: is there a connection?
