52 citations · 72 across the 11 of their papers we have counts for
8 papers · 1 filter
Vine dependence graphs with latent variables as summaries for gene expression data
Xinyao Fan, Harry Joe, Yongjin Park
The advent of high-throughput sequencing technologies has lead to vast comparative genome sequences. The construction of gene-gene interaction networks or dependence graphs on the…
Margin-closed vector autoregressive time series models
Lin Zhang, Harry Joe, Natalia Nolde
Conditions are obtained for a Gaussian vector autoregressive time series of order , VAR(), to have univariate margins that are autoregressive of order or lower-dimensiona…
High-dimensional factor copula models with estimation of latent variables
Xinyao Fan, Harry Joe
Factor models are a parsimonious way to explain the dependence of variables using several latent variables. In Gaussian 1-factor and structural factor models (such as bi-factor, ob…
Predicting Times to Event Based on Vine Copula Models
Shenyi Pan, Harry Joe
In statistics, time-to-event analysis methods traditionally focus on the estimation of hazards. In recent years, machine learning methods have been proposed to directly predict the…
Conditional Inferences Based on Vine Copulas with Applications to Credit Spread Data of Corporate Bonds
Shenyi Pan, Harry Joe, Guofu Li
Understanding the dependence relationship of credit spreads of corporate bonds is important for risk management. Vine copula models with tail dependence are used to analyze a credi…
Prediction based on conditional distributions of vine copulas
Bo Chang, Harry Joe
Vine copulas are a flexible tool for multivariate non-Gaussian distributions. For data from an observational study where the explanatory variables and response variables are measur…
Intermediate Tail Dependence: A Review and Some New Results
Lei Hua, Harry Joe
The concept of intermediate tail dependence is useful if one wants to quantify the degree of positive dependence in the tails when there is no strong evidence of presence of the us…
Simplified Pair Copula Constructions --- Limits and Extensions
Jakob Stöber, Harry Joe, Claudia Czado
So called pair copula constructions (PCCs), specifying multivariate distributions only in terms of bivariate building blocks (pair copulas), constitute a flexible class of dependen…