In her proposal Claudia Maienborn attempts to provide evidence above all for the following basic claims: First, stative verbal expressions, regardless of whether they represent stage-level or individual-level predicates, pattern with eventive expressions in introducing a hidden referential argument which can be located in time and may serve as an antecedent for anaphoric reference. What separat...

Empirical studies show that there is stronger dependency between large losses than large profit in financial market, which undermine the performance of using symmetric distribution for modeling these asymmetric. That is why the assuming normal joint distribution of returns is not suitable because of considering the linier dependence, and can be lead to inappropriate estimate of VaR. Copula theo...

In order to evaluate the importance of higher-order correlations in neural spike count codes, flexible statistical models of dependent multivariate spike counts are required. Copula families, parametric multivariate distributions that represent dependencies, can be applied to construct such models. We introduce the Frank mixture family as a new copula family that has separate parameters for all...

This article examines the ability of time-varying Gaussian and Student t copulas to accurately predict the probability of joint extreme co-movements in stock index returns. Using a sample of more than 20 years of daily return observations of the Eurostoxx 50 and Dow Jones Industrial 30 stock indices, Gaussian and Student t copulas are calibrated daily on a rolling window of the 250 most recent ...

Imipramine-induced ex copula ejaculates (11) and fractionated in copula ejaculates were collected from each of 5 pony stallions for freezing in 5-ml straws (6), using a modified Kenney glucose skim-milk extender (2). Initial post-thaw total and progressive motilities and daily post-thaw total and progressive motilities, as well as the number of days to reach 0 progressively motile spermatozoa, ...

Goodness-of-fit tests are a fundamental element in the copula-based modeling of multivariate continuous distributions. Among the different procedures proposed in the literature, recent large scale simulations suggest that one of the most powerful tests is based on the empirical process comparing the empirical copula with a parametric estimate of the copula derived under the null hypothesis. As ...

Recently Chen and Fan (2003a) introduced a new class of semiparametric copula-based multivariate dynamic (SCOMDY) models. A SCOMDY model specifies the conditional mean and the conditional variance of a multivariate time series parametrically (such as VAR, GARCH), but specifies the multivariate distribution of the standardized innovation semiparametrically as a parametric copula evaluated at non...

We tackle the problem of multi-task learning with copula process. Multivariable prediction in spatial and spatialtemporal processes such as natural resource estimation and pollution monitoring have been typically addressed using techniques based on Gaussian processes and co-Kriging. While the Gaussian prior assumption is convenient from analytical and computational perspectives, nature is domin...

We describe a model that takes into account the tail dependence present in a large set of historical risk factor data using the modern concept of copulas. We extend the popular t-copula to obtain a new grouped t-copula which describes more accurately the dependence among risk factors of different classes. We explain how to estimate the parameters of the grouped t-copula and apply the method to ...