3 papers
stat.ME2018
A partial correlation vine based approach for modeling and forecasting multivariate volatility time-series
Nicole Barthel, Claudia Czado, Yarema Okhrin
A novel approach for dynamic modeling and forecasting of realized covariance matrices is proposed. Realized variances and realized correlation matrices are jointly estimated. The o…
stat.ME2017
Dependence modeling for recurrent event times subject to right-censoring with D-vine copulas
Nicole Barthel, Candida Geerdens, Claudia Czado +1
In many time-to-event studies, the event of interest is recurrent. Here, the data for each sample unit corresponds to a series of gap times between the subsequent events. Given a l…
stat.AP2016
Vine copula based likelihood estimation of dependence patterns in multivariate event time data
Nicole Barthel, Candida Geerdens, Matthias Killiches +2
In many studies multivariate event time data are generated from clusters having a possibly complex association pattern. Flexible models are needed to capture this dependence. Vine…