VineCopula - Statistical Inference of Vine Copulas
Provides tools for the statistical analysis of regular vine copula models, see Aas et al. (2009) <doi:10.1016/j.insmatheco.2007.02.001> and Dissman et al. (2013) <doi:10.1016/j.csda.2012.08.010>. The package includes tools for parameter estimation, model selection, simulation, goodness-of-fit tests, and visualization. Tools for estimation, selection and exploratory data analysis of bivariate copula models are also provided.
Last updated
copulaestimationstatisticsvine
10.89 score 100 stars 24 dependents 578 scripts 4.4k downloadsRcppThread - R-Friendly Threading in C++
Provides a C++11-style thread class and thread pool that can safely be interrupted from R. See Nagler (2021) <doi:10.18637/jss.v097.c01>.
Last updated
cpp
10.10 score 62 stars 119 dependents 11 scripts 10k downloadskde1d - Univariate Kernel Density Estimation
Provides an efficient implementation of univariate local polynomial kernel density estimators that can handle bounded, discrete, and zero-inflated data. See Geenens and Wang (2018) <doi:10.48550/arXiv.1602.04862>, Geenens (2014) <doi:10.48550/arXiv.1303.4121>, Nagler (2018a) <doi:10.48550/arXiv.1704.07457>, Nagler (2018b) <doi:10.48550/arXiv.1705.05431>.
Last updated
cpp
7.30 score 14 stars 17 dependents 84 scripts 1.7k downloadswdm - Weighted Dependence Measures
Provides efficient implementations of weighted dependence measures and related asymptotic tests for independence. Implemented measures are the Pearson correlation, Spearman's rho, Kendall's tau, Blomqvist's beta, Hoeffding's D, and Chatterjee's xi; see, e.g., Nelsen (2006) <doi:10.1007/0-387-28678-0>, Hollander et al. (2015, ISBN:9780470387375), and Chatterjee (2021) <doi:10.1080/01621459.2020.1758115>.
Last updated
dependencestatisticscpp
6.05 score 3 stars 20 dependents 19 scripts 3.3k downloadskdecopula - Kernel Smoothing for Bivariate Copula Densities
Provides fast implementations of kernel smoothing techniques for bivariate copula densities, in particular density estimation and resampling, see Nagler (2018) <doi:10.18637/jss.v084.i07>.
Last updated
openblascpp
6.04 score 9 stars 1 dependents 47 scripts 1.7k downloadsvinereg - D-Vine Quantile Regression
Implements D-vine quantile regression models with parametric or nonparametric pair-copulas. See Kraus and Czado (2017) <doi:10.1016/j.csda.2016.12.009> and Schallhorn et al. (2017) <doi:10.48550/arXiv.1705.08310>.
Last updated
copulaestimationstatisticsvinecpp
6.02 score 11 stars 32 scripts 418 downloadssvines - Stationary Vine Copula Models
Provides functionality to fit and simulate from stationary vine copula models for time series, see Nagler et al. (2022) <doi:10.1016/j.jeconom.2021.11.015>.
Last updated
cpp
5.08 score 4 stars 9 scripts 459 downloadskdevine - Multivariate Kernel Density Estimation with Vine Copulas
Implements the vine copula based kernel density estimator of Nagler and Czado (2016) <doi:10.1016/j.jmva.2016.07.003>. The estimator does not suffer from the curse of dimensionality and is therefore well suited for high-dimensional applications.
Last updated
cpp
4.47 score 16 stars 37 scripts 288 downloadsVC2copula - Extend the 'copula' Package with Families and Models from 'VineCopula'
Provides new classes for (rotated) BB1, BB6, BB7, BB8, and Tawn copulas, extends the existing Gumbel and Clayton families with rotations, and allows to set up a vine copula model using the 'copula' API. Corresponding objects from the 'VineCopula' API can easily be converted.
Last updated
3.53 score 4 stars 17 scripts 299 downloadscctools - Tools for the Continuous Convolution Trick in Nonparametric Estimation
Implements the uniform scaled beta distribution and the continuous convolution kernel density estimator.
Last updated
cpp
3.18 score 1 dependents 8 scripts 405 downloads