vines - Multivariate Dependence Modeling with Vines
Implementation of the vine graphical model for building high-dimensional probability distributions as a factorization of bivariate copulas and marginal density functions. This package provides S4 classes for vines (C-vines and D-vines) and methods for inference, goodness-of-fit tests, density/distribution function evaluation, and simulation.
Last updated 2 months ago
3.48 score 1 dependents 10 scripts 345 downloadscopulaedas - Estimation of Distribution Algorithms Based on Copulas
Provides a platform where EDAs (estimation of distribution algorithms) based on copulas can be implemented and studied. The package offers complete implementations of various EDAs based on copulas and vines, a group of well-known optimization problems, and utility functions to study the performance of the algorithms. Newly developed EDAs can be easily integrated into the package by extending an S4 class with generic functions for their main components.
Last updated 4 years ago
3.26 score 2 stars 18 scripts 291 downloads