Matlab toolbox for canonical vine copula trees with mixed continuous and discrete marginals

Causal discovery from mixed data with missing values.

Multivariate Environmental Statistics (BEE6300) R Code

Inference for Gaussian copula factor models and its application to causal discovery.

In this project, we predict the probability of occurrence of risk in the Indian territory, based on the historical data of precipitation and temperature between the years 1951 - 2015

The repo contains the main topics carried out in my master's thesis on operational risk. In particular, it is described how to implement the so called Loss Distribution Approach (LDA), which is considered the state-of-the-art method to compute capital charge among large banks.

Robust Estimation of Copulas by Maximum Mean Discrepancy

Examples of scheduled jobs estimating copulas at www.microprediction.org

Copula fitting in Python.

Python package for canonical vine copula trees with mixed continuous and discrete marginals

The Quant Copula Playground is a Shiny application designed for everyone interested in exploring the dependencies between stock returns using various copula models. This application is inspired by seminal works in the field of copulas, particularly "An Introduction to Copulas" by Roger B. Nelsen.

Gumbel, Clayton, Frank, and Independence copula that use on Weibull distribution.

Multivariate data modelling with Copulas in Python

Copula-based Hidden Markov Model (HMM) to decode tactics in a football match. Final project for the Probabilistic Machine Learning course of the MSc degree in Data Science and Artificial Intelligence (DSAI), University of Trieste

Simulation of Partition-of-Unity copulas in R, e.g. for the purpose of modeling risk or for the creation of synthetic data based on restricted datasets

Portfolio credit risk modeling

Discrete checkerboard copula modeling and implementation of new scoring methods pertaining to ordinal and categorical discrete data.