activity
20152026
most citedEvading the curse of dimensionality in nonparametric density estimation with simplified vine copulas

151 citations · 321 across the 18 of their papers we have counts for

collaborators
Showing 2018Show all

5 papers · 1 filter

stat.AP2018★ 12 cited

Vine copula based post-processing of ensemble forecasts for temperature

Annette Möller, Ludovica Spazzini, Daniel Kraus +2

Today weather forecasting is conducted using numerical weather prediction (NWP) models, consisting of a set of differential equations describing the dynamics of the atmosphere. The…

stat.CO2018

R friendly multi-threading in C++

Thomas Nagler

Calling multi-threaded C++ code from R has its perils. Since the R interpreter is single-threaded, one must not check for user interruptions or print to the R console from multiple…

stat.AP2018

A Statistical Simulation Method for Joint Time Series of Non-stationary Hourly Wave Parameters

Wiebke S. Jäger, Thomas Nagler, Claudia Czado +1

Statistically simulated time series of wave parameters are required for many coastal and offshore engineering applications, often at the resolution of approximately one hour. Vario…

stat.ME2018★ 2 cited

Solving estimating equations with copulas

Thomas Nagler, Thibault Vatter

Thanks to their ability to capture complex dependence structures, copulas are frequently used to glue random variables into a joint model with arbitrary marginal distributions. Mor…

stat.ME2018

Model selection in sparse high-dimensional vine copula models with application to portfolio risk

Thomas Nagler, Christian Bumann, Claudia Czado

Vine copulas allow to build flexible dependence models for an arbitrary number of variables using only bivariate building blocks. The number of parameters in a vine copula model in…