High-dimensional data sets are often available in genome-enabled predict...
This paper proposes a novel method for testing observability in Gaussian...
The RTS smoother is widely used for state estimation and it is utilized ...
In aviation safety, runway overruns are of great importance because they...
The statistical analysis of univariate quantiles is a well developed res...
While there is considerable effort to identify signaling pathways using
...
Consider a survival time T that is subject to random right censoring, an...
Quantile regression is a field with steadily growing importance in
stati...
The majority of finite mixture models suffer from not allowing asymmetri...
We propose a class of dynamic vine copula models. This is an extension o...
In this paper we propose a flexible class of multivariate nonlinear
non-...
Air pollution is a serious issue that currently affects many industrial
...
Latent autoregressive processes are a popular choice to model time varyi...
Today weather forecasting is conducted using numerical weather predictio...
Statistically simulated time series of wave parameters are required for ...
Single factor models are used in finance to model the joint behaviour of...
A novel approach for dynamic modeling and forecasting of realized covari...
Vine copulas allow to build flexible dependence models for an arbitrary
...
In several time-to-event studies, the event of interest occurs more than...
To model high dimensional data, Gaussian methods are widely used since t...