Received: 2019-02-20
Accepted: 2019-09-19
Published Online: 2019-11-11
© 2019 Rachid Bentoumi et al., published by De Gruyter
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Keywords for this article
Length-biased sampling;
covariate distribution;
length-biased distribution;
information gain;
dependence measure;
kernel density estimation;
copulas
Creative Commons
BY 4.0
Articles in the same Issue
- Special Issue: Heavy Tails and Dependence
- Volatility filtering in estimation of kurtosis (and variance)
- Structural change in the link between oil and the European stock market: implications for risk management
- Copula multivariate GARCH model with constrained Hamiltonian Monte Carlo
- Probability of ruin in discrete insurance risk model with dependent Pareto claims
- Fitting heavy-tailed mixture models with CVaR constraints
- Regular articles
- Modelling cascading effects for systemic risk: Properties of the Freund copula
- A simple proof of Pitman–Yor’s Chinese restaurant process from its stick-breaking representation
- On the lower bound of Spearman’s footrule
- Exponential inequalities for nonstationary Markov chains
- New copulas based on general partitions-of-unity (part III) — the continuous case
- Simulation algorithms for hierarchical Archimedean copulas beyond the completely monotone case
- A latent class analysis towards stability and changes in breadwinning patterns among coupled households
- Copulas, stable tail dependence functions, and multivariate monotonicity
- On a class of norms generated by nonnegative integrable distributions
- On the asymptotic covariance of the multivariate empirical copula process
- On kernel-based estimation of conditional Kendall’s tau: finite-distance bounds and asymptotic behavior
- On Copula-Itô processes
- Dependence measure for length-biased survival data using copulas
- Optimal bandwidth selection for recursive Gumbel kernel density estimators
- Estimation of the tail-index in a conditional location-scale family of heavy-tailed distributions
- Interview Article
- The world of vines