R: Estimation and Inference for Conditional Copula Models

# Estimation and Inference for Conditional Copula Models

## Documentation for package ‘CondCopulas’ version 0.2.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

bCond.estParamCopula | Estimation of the conditional parameters of a parametric conditional copula with discrete conditioning events.
bCond.pobs | Computing the pseudo-observations in case of discrete conditioning events
bCond.simpA.CKT | Function for testing the simplifying assumption with data-driven box-type conditioning events
bCond.simpA.param | Test of the assumption that a conditional copulas does not vary through a list of discrete conditioning events
bCond.treeCKT | Construct a binary tree for the modeling the conditional Kendall's tau
CKT.estimate | Estimation of conditional Kendall's tau between two variables X1 and X2 given Z = z
CKT.fit.GLM | Estimation of conditional Kendall's taus by penalized GLM
CKT.fit.nNets | Estimation of conditional Kendall's taus by model averaging of neural networks
CKT.fit.randomForest | Fit a Random Forest that can be used for the estimation of conditional Kendall's tau.
CKT.fit.tree | Estimation of conditional Kendall's taus using a classification tree
CKT.hCV.Kfolds | Choose the bandwidth for kernel estimation of conditional Kendall's tau using cross-validation
CKT.hCV.l1out | Choose the bandwidth for kernel estimation of conditional Kendall's tau using cross-validation
CKT.kendallReg.fit | Fit Kendall's regression, a GLM-type model for conditional Kendall's tau
CKT.KendallReg.LambdaCV | Kendall's regression: choice of the penalization parameter by K-folds cross-validation
CKT.kendallReg.predict | Fit Kendall's regression, a GLM-type model for conditional Kendall's tau
CKT.kernel | Estimation of conditional Kendall's tau using kernel smoothing
CKT.predict.GLM | Estimation of conditional Kendall's taus by penalized GLM
CKT.predict.kNN | Prediction of conditional Kendall's tau using nearest neighbors
CKT.predict.nNets | Predict the values of conditional Kendall's tau using Model Averaging of Neural Networks
CKT.predict.randomForest | Fit a Random Forest that can be used for the estimation of conditional Kendall's tau.
CKT.predict.tree | Estimation of conditional Kendall's taus using a classification tree
CKTmatrix.kernel | Estimate the conditional Kendall's tau matrix at different conditioning points
coef.simpA_kendallReg_test | Test of the simplifying assumption using the constancy of conditional Kendall's tau
computeKernelMatrix | Computing the kernel matrix
computeMatrixSignPairs | Compute the matrix of signs of pairs
confint.estimated_CKT_kernel | Methods for class 'estimated_CKT_kernel'
conv_treeCKT | Converting to matrix of indicators / matrix of conditional Kendall's tau
datasetPairs | Construct a dataset of pairs of observations for the estimation of conditional Kendall's tau
estimateCondCDF_matrix | Compute kernel-based conditional marginal (univariate) cdfs
estimateCondCDF_vec | Compute kernel-based conditional marginal (univariate) cdfs
estimateCondQuantiles | Compute kernel-based conditional quantiles
estimateNPCondCopula | Compute a kernel-based estimator of the conditional copula
estimateParCondCopula | Estimation of parametric conditional copulas
estimateParCondCopula_ZIJ | Estimation of parametric conditional copulas
matrixInd2matrixCKT | Converting to matrix of indicators / matrix of conditional Kendall's tau
measures_nonsimplifyingness_NP | Compute a measure of non-simplifyingness based on non-parametric estimation of the conditional copula
plot.estimated_CKT_kernel | Methods for class 'estimated_CKT_kernel'
plot.simpA_kendallReg_test | Test of the simplifying assumption using the constancy of conditional Kendall's tau
print.simpA_kendallReg_test | Test of the simplifying assumption using the constancy of conditional Kendall's tau
se | Standard Error of Model Coefficients
se.estimated_CKT_kernel | Methods for class 'estimated_CKT_kernel'
se.simpA_kendallReg_test | Test of the simplifying assumption using the constancy of conditional Kendall's tau
simpA.kendallReg | Test of the simplifying assumption using the constancy of conditional Kendall's tau
simpA.NP | Nonparametric testing of the simplifying assumption
simpA.param | Semiparametric testing of the simplifying assumption
treeCKT2matrixCKT | Converting to matrix of indicators / matrix of conditional Kendall's tau
treeCKT2matrixInd | Converting to matrix of indicators / matrix of conditional Kendall's tau
vcov.simpA_kendallReg_test | Test of the simplifying assumption using the constancy of conditional Kendall's tau