Pages that link to "Item:Q1848964"
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The following pages link to Vines -- a new graphical model for dependent random variables. (Q1848964):
Displaying 50 items.
- 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)
- Robust omega ratio optimization using regular vines (Q2047199) (← links)
- Copula-based Black-Litterman portfolio optimization (Q2060420) (← links)
- Customized structural elicitation (Q2086348) (← 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)
- Variational inference with vine copulas: an efficient approach for Bayesian computer model calibration (Q2110192) (← links)
- Mixed value-at-risk and its numerical investigation (Q2137621) (← links)
- Regular vines with strongly chordal pattern of (conditional) independence (Q2142996) (← 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)
- On identification and non-normal simulation in ordinal covariance and item response models (Q2177739) (← links)
- Surrogate modeling of high-dimensional problems via data-driven polynomial chaos expansions and sparse partial least square (Q2180429) (← links)
- Modelling an energy market with Bayesian networks for non-normal data (Q2183558) (← 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)
- Copula index for detecting dependence and monotonicity between stochastic signals (Q2213108) (← links)
- Vine copula regression for observational studies (Q2218559) (← links)
- A Bayesian hierarchical copula model (Q2219218) (← links)
- A copula-based method of classifying individuals into binary disease categories using dependent biomarkers (Q2220308) (← 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)
- Explaining predictive models using Shapley values and non-parametric vine copulas (Q2236381) (← links)
- Multi-factor dependence modelling with specified marginals and structured association in large-scale project risk assessment (Q2242316) (← links)
- Crisis and risk dependencies (Q2253371) (← links)
- Measuring rank correlation coefficients between financial time series: a GARCH-copula based sequence alignment algorithm (Q2255953) (← links)
- Estimating standard errors in regular vine copula models (Q2259341) (← links)
- Copula selection for graphical models in continuous estimation of distribution algorithms (Q2259747) (← links)
- A journey beyond the Gaussian world. An interview with Harry Joe (Q2283651) (← links)
- M-vine decomposition and VAR(1) models (Q2288813) (← links)
- Economic and financial risk factors, copula dependence and risk sensitivity of large multi-asset class portfolios (Q2288967) (← links)
- Distribution modeling for reliability analysis: impact of multiple dependences and probability model selection (Q2295880) (← links)
- Semiparametric bivariate modelling with flexible extremal dependence (Q2302487) (← links)
- Spatial pair-copula model of grade for an anisotropic gold deposit (Q2325285) (← links)
- Selection of sparse vine copulas in high dimensions with the Lasso (Q2329765) (← links)
- Of copulas, quantiles, ranks and spectra: an \(L_{1}\)-approach to spectral analysis (Q2348726) (← links)
- Preface to special issue on high-dimensional dependence and copulas (Q2350034) (← links)
- Sampling, conditionalizing, counting, merging, searching regular vines (Q2350035) (← links)
- Truncation of vine copulas using fit indices (Q2350036) (← links)
- Efficient information based goodness-of-fit tests for vine copula models with fixed margins: a comprehensive review (Q2350037) (← links)
- Spatial composite likelihood inference using local C-vines (Q2350040) (← links)
- Modeling dependence structure among European markets and among Asian-Pacific markets: a regime switching regular vine copula approach (Q2358171) (← links)
- A practical model of Heineken's bottle filling line with dependent failures (Q2387237) (← links)
- On copula-based conditional quantile estimators (Q2407485) (← links)
- Dependence modelling in ultra high dimensions with vine copulas and the graphical Lasso (Q2416782) (← links)
