Pages that link to "Item:Q80563"

The following pages link to Pair-copula constructions of multiple dependence (Q80563):

Displaying 50 items.

• Heterogeneous tail generalized COMFORT modeling via Cholesky decomposition (Q2001089) (← links)
• Model selection in sparse high-dimensional vine copula models with an application to portfolio risk (Q2001097) (← links)
• Prediction based on conditional distributions of vine copulas (Q2002717) (← links)
• Conditional copula simulation for systemic risk stress testing (Q2015640) (← links)
• Total loss estimation using copula-based regression models (Q2015655) (← links)
• A copula-based GLMM model for multivariate longitudinal data with mixed-types of responses (Q2023800) (← links)
• pyvine: the Python package for regular vine copula modeling, sampling and testing (Q2023903) (← links)
• A geometric investigation into the tail dependence of vine copulas (Q2034451) (← links)
• Modelling mortality dependence: an application of dynamic vine copula (Q2038244) (← links)
• A mixture of regular vines for multiple dependencies (Q2039146) (← links)
• Multivariate distributions of correlated binary variables generated by pair-copulas (Q2040911) (← links)
• How simplifying and flexible is the simplifying assumption in pair-copula constructions -- analytic answers in dimension three and a glimpse beyond (Q2044366) (← links)
• Counterdiagonal/nonpositive tail dependence in vine copula constructions: application to portfolio management (Q2059101) (← links)
• Copula-based Black-Litterman portfolio optimization (Q2060420) (← links)
• Robust and efficient estimating equations for longitudinal data partial linear models and its applications (Q2062374) (← links)
• Statistical dependence: beyond Pearson's \(\rho\) (Q2075797) (← links)
• New perspectives on knockoffs construction (Q2095099) (← links)
• Bayesian ridge estimators based on copula-based joint prior distributions for regression coefficients (Q2095777) (← links)
• Conditional empirical copula processes and generalized measures of association (Q2106777) (← links)
• Modeling spatial tail dependence with Cauchy convolution processes (Q2106793) (← links)
• Copula-based measures of asymmetry between the lower and upper tail probabilities (Q2110347) (← links)
• Mixed value-at-risk and its numerical investigation (Q2137621) (← links)
• A new class of copula regression models for modelling multivariate heavy-tailed data (Q2138631) (← links)
• Regular vines with strongly chordal pattern of (conditional) independence (Q2142996) (← links)
• Technical and allocative inefficiency in production systems: a vine copula approach (Q2148729) (← links)
• An optimal reinsurance simulation model for non-life insurance in the Solvency II framework (Q2157214) (← links)
• Modeling vine-production function: an approach based on vine copula (Q2162548) (← links)
• Analysis of ordinal and continuous longitudinal responses using pair copula construction (Q2168557) (← links)
• Structural change in the link between oil and the European stock market: implications for risk management (Q2178931) (← links)
• On the quantification and efficient propagation of imprecise probabilities with copula dependence (Q2191243) (← links)
• Risk aggregation in non-life insurance: standard models vs. internal models (Q2212172) (← links)
• Vine copula regression for observational studies (Q2218559) (← links)
• A transition model for analyzing multivariate longitudinal data using Gaussian copula approach (Q2218560) (← links)
• A Bayesian hierarchical copula model (Q2219218) (← links)
• On structural properties of an asymmetric copula family and its statistical implication (Q2219344) (← links)
• Measuring market and credit risk under Solvency II: evaluation of the standard technique versus internal models for stock and bond markets (Q2219623) (← links)
• Data-driven polynomial chaos expansion for machine learning regression (Q2220634) (← links)
• Ordering results for elliptical distributions with applications to risk bounds (Q2222233) (← links)
• Pair-copula models for analyzing family data (Q2223156) (← links)
• Conditional normal extreme-value copulas (Q2231306) (← links)
• Explaining predictive models using Shapley values and non-parametric vine copulas (Q2236381) (← links)
• Detecting departures from meta-ellipticity for multivariate stationary time series (Q2236384) (← links)
• Model selection of copulas: AIC versus a cross validation copula information criterion (Q2251716) (← links)
• Crisis and risk dependencies (Q2253371) (← links)
• Estimating standard errors in regular vine copula models (Q2259341) (← links)
• Penalized marginal likelihood estimation of finite mixtures of Archimedean copulas (Q2259718) (← links)
• Copula selection for graphical models in continuous estimation of distribution algorithms (Q2259747) (← links)
• On the quantification of aleatory and epistemic uncertainty using sliced-normal distributions (Q2278545) (← links)
• Multivariate upper semilinear copulas (Q2279699) (← links)
• Ordering risk bounds in factor models (Q2283650) (← links)