Vine copula regression for observational studies
DOI10.1007/s10182-019-00353-5zbMath1457.62153OpenAlexW2949023603WikidataQ127746381 ScholiaQ127746381MaRDI QIDQ2218559
Bo Chang, Roger M. Cooke, Joe, Harry
Publication date: 15 January 2021
Published in: AStA. Advances in Statistical Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10182-019-00353-5
heteroscedasticityGaussian copulabreastfeedingregular vineIQnational longitudinal study of youthpitfalls of regression inference
Applications of statistics to social sciences (62P25) Characterization and structure theory for multivariate probability distributions; copulas (62H05) General nonlinear regression (62J02) Causal inference from observational studies (62D20)
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- Pair-copula constructions of multiple dependence
- Selecting and estimating regular vine copulae and application to financial returns
- D-vine copula based quantile regression
- Dependence properties of conditional distributions of some copula models
- Comorbidity of chronic diseases in the elderly: patterns identified by a copula design for mixed responses
- Vines -- a new graphical model for dependent random variables.
- Vine copulas with asymmetric tail dependence and applications to financial return data
- Prediction based on conditional distributions of vine copulas
- Probability density decomposition for conditionally dependent random variables modeled by vines
- Sampling, conditionalizing, counting, merging, searching regular vines
- Truncation of vine copulas using fit indices
- Conditional quantiles and tail dependence
- Dependence Modeling with Copulas
- Truncated regular vines in high dimensions with application to financial data
- Response Surfaces, Mixtures, and Ridge Analyses
- Developing Econometrics
- Transformation of the Independent Variables
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