Estimation and Inference for Conditional Copula Models


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Documentation for package ‘CondCopulas’ version 0.1.2

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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
computeKernelMatrix Computing the kernel matrix
computeMatrixSignPairs Compute the matrix of signs of pairs
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
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