Estimation and Inference for Conditional Copula Models
Estimation of the conditional parameters of a parametric conditional c...
Computing the pseudo-observations in case of discrete conditioning eve...
Function for testing the simplifying assumption with data-driven box-t...
Test of the assumption that a conditional copulas does not vary throug...
Construct a binary tree for the modeling the conditional Kendall's tau
Estimation of conditional Kendall's tau between two variables X1 and X...
Estimation of conditional Kendall's taus by penalized GLM
Predict the values of conditional Kendall's tau using Model Averaging ...
Estimation of conditional Kendall's taus by model averaging of neural ...
Fit a Random Forest that can be used for the estimation of conditional...
Estimation of conditional Kendall's taus using a classification tree
Choose the bandwidth for kernel estimation of conditional Kendall's ta...
Fit Kendall's regression, a GLM-type model for conditional Kendall's t...
Kendall's regression: choice of the penalization parameter by K-folds ...
Estimation of conditional Kendall's tau using kernel smoothing
Prediction of conditional Kendall's tau using nearest neighbors
Estimate the conditional Kendall's tau matrix at different conditionin...
Computing the kernel matrix
Compute the matrix of signs of pairs
Converting to matrix of indicators / matrix of conditional Kendall's t...
Construct a dataset of pairs of observations for the estimation of con...
Compute kernel-based conditional marginal (univariate) cdfs
Compute kernel-based conditional marginal (univariate) cdfs
Compute kernel-based conditional quantiles
Compute a kernel-based estimator of the conditional copula
Estimation of parametric conditional copulas
Compute a measure of non-simplifyingness based on non-parametric estim...
Methods for class estimated_CKT_kernel
Standard Error of Model Coefficients
Test of the simplifying assumption using the constancy of conditional ...
Nonparametric testing of the simplifying assumption
Semiparametric testing of the simplifying assumption
Provides functions for the estimation of conditional copulas models, various estimators of conditional Kendall's tau (proposed in Derumigny and Fermanian (2019a, 2019b, 2020) <doi:10.1515/demo-2019-0016>, <doi:10.1016/j.csda.2019.01.013>, <doi:10.1016/j.jmva.2020.104610>), test procedures for the simplifying assumption (proposed in Derumigny and Fermanian (2017) <doi:10.1515/demo-2017-0011> and Derumigny, Fermanian and Min (2022) <doi:10.1002/cjs.11742>), and measures of non-simplifyingness (proposed in Derumigny (2025) <doi:10.48550/arXiv.2504.07704>).
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