The following pages link to Dependence Modeling with Copulas (Q3190362):
Displaying 50 items.
- Covariance model simulation using regular vines (Q1695739) (← links)
- Dependent risk models with Archimedean copulas: a computational strategy based on common mixtures and applications (Q1697215) (← links)
- \(D_s\)-optimality in copula models (Q1697867) (← links)
- Vine copulas for mixed data: multi-view clustering for mixed data beyond meta-Gaussian dependencies (Q1698838) (← links)
- On tail dependence coefficients of transformed multivariate Archimedean copulas (Q1699336) (← links)
- Model distances for vine copulas in high dimensions (Q1702012) (← links)
- Estimating non-simplified vine copulas using penalized splines (Q1702016) (← links)
- Vine copula approximation: a generic method for coping with conditional dependence (Q1702298) (← links)
- An asymptotic characterization of hidden tail credit risk with actuarial applications (Q1707554) (← links)
- Analyzing dependent data with vine copulas. A practical guide with R (Q1738351) (← links)
- Copula theory and probabilistic sensitivity analysis: is there a connection? (Q1740560) (← links)
- Multivariate extreme value copulas with factor and tree dependence structures (Q1744180) (← links)
- Efron's monotonicity property for measures on \(\mathbb{R}^2\) (Q1749994) (← links)
- Expert judgement for dependence in probabilistic modelling: a systematic literature review and future research directions (Q1751712) (← links)
- Extremal dependence concepts (Q1790300) (← links)
- Probabilistic analysis of solar power supply using D-vine copulas based on meteorological variables (Q1979682) (← links)
- Sequential truncation of \(R\)-vine copula mixture model for high-dimensional datasets (Q1980359) (← links)
- Non-exchangeability of copulas arising from shock models (Q2000611) (← links)
- Heterogeneous tail generalized COMFORT modeling via Cholesky decomposition (Q2001089) (← links)
- Nonparametric estimation of multivariate tail probabilities and tail dependence coefficients (Q2001093) (← links)
- Model selection in sparse high-dimensional vine copula models with an application to portfolio risk (Q2001097) (← links)
- Introduction to extreme value theory: applications to risk analysis and management (Q2001261) (← links)
- Prediction based on conditional distributions of vine copulas (Q2002717) (← links)
- A partial correlation vine based approach for modeling and forecasting multivariate volatility time-series (Q2008095) (← links)
- Generalized Pareto copulas: a key to multivariate extremes (Q2008230) (← links)
- Bounds on distributional treatment effect parameters using panel data with an application on job displacement (Q2024455) (← links)
- Reflected maxmin copulas and modeling quadrant subindependence (Q2037445) (← links)
- A mixture of regular vines for multiple dependencies (Q2039146) (← links)
- Multivariate distributions of correlated binary variables generated by pair-copulas (Q2040911) (← links)
- Dependence structure estimation using copula recursive trees (Q2048120) (← links)
- Inducing a desired value of correlation between two point-scale variables: a two-step procedure using copulas (Q2058546) (← links)
- Copula-based Black-Litterman portfolio optimization (Q2060420) (← links)
- On copulas of self-similar Ito processes (Q2063748) (← links)
- New results on perturbation-based copulas (Q2063752) (← links)
- Testing for changes in the tail behavior of Brown-Resnick Pareto processes (Q2066970) (← links)
- Effective estimation algorithm for parameters of multivariate Farlie-Gumbel-Morgenstern copula (Q2068951) (← links)
- Multivariate failure time distributions derived from shared frailty and copulas (Q2068954) (← links)
- Sample selection models with monotone control functions (Q2074593) (← links)
- Statistical dependence: beyond Pearson's \(\rho\) (Q2075797) (← links)
- Baire category results for stochastic orders (Q2081243) (← links)
- Parameter estimation for multi-state coherent series and parallel systems with positively quadrant dependent models (Q2082345) (← links)
- Distortion representations of multivariate distributions (Q2082487) (← links)
- Total positivity of copulas from a Markov kernel perspective (Q2084845) (← links)
- Multiple inflated negative binomial regression for correlated multivariate count data (Q2097688) (← links)
- Copula-based measures of asymmetry between the lower and upper tail probabilities (Q2110347) (← links)
- Selection of mixed copula for association modeling with tied observations (Q2111315) (← links)
- Bayesian empirical likelihood inference for the generalized binomial AR(1) model (Q2111947) (← links)
- Limitations and performance of three approaches to Bayesian inference for Gaussian copula regression models of discrete data (Q2135899) (← links)
- Joint inference on extreme expectiles for multivariate heavy-tailed distributions (Q2137005) (← links)
- A new class of copula regression models for modelling multivariate heavy-tailed data (Q2138631) (← links)
