In stochastic volatility (SV) models, asset returns conditional on the latent volatility are usually assumed to have a normal, Student-t or exponential power (EP) distribution. An earlier study uses a generalised t (GT) distribution for the conditional returns and the results indicate that the...

In this paper we use Markov chain Monte Carlo (MCMC) methods in order to estimate and compare GARCH models from a Bayesian perspective. We allow for possibly heavy tailed and asymmetric distributions in the error term. We use a general method proposed in the literature to introduce skewness into...

In this paper we propose to use Markov chain Monte Carlo methods to estimate the parameters of stochastic volatility models with several factors varying at different time scales. The originality of our approach, in contrast with classical factor models is the identification of two factors...

We show that sampling with a biased Metropolis scheme is essentially equivalent to using the heatbath algorithm. However, the biased Metropolis method can also be applied when an efficient heatbath algorithm does not exist. This is first illustrated with an example from high energy physics...

Global sensitivity analysis is used to quantify the influence of input variables on a numerical model output. Sobol’ indices are now classical sensitivity measures. However their estimation requires a large number of model evaluations, especially when interaction effects are of interest....

We consider linear dynamical systems defined by differential algebraic equations. The associated input–output behaviour is given by a transfer function in the frequency domain. Physical parameters of the dynamical system are replaced by random variables to quantify uncertainties. We analyse...

This paper deals with homogenization of microscopically heterogeneous media which are subjected to finite deformations. The updated Lagrangian scheme is applied to obtain linear subproblems which can be homogenized using the two-scale convergence. Microscopic equations and homogenized stiffness...

We address in this paper the efficient estimation of sensitivity coefficients by Monte Carlo simulations. In the context of geological performance for the risk assessment of radioactive waste repositories, a recent non-analog Monte Carlo simulation [1] based on an integral equation for the...

For the evaluation of data from stimulus response experiments dynamic metabolic network models are generated. With an increase of reaction steps and regulatory interdependencies the amount of the simulation data becomes hard to handle. In this paper, we present the application and extension of...

The Davis Growth Model (a dynamic steer growth model encompassing 4 fat deposition models) is currently being used by the phenotypic prediction program of the Cooperative Research Centre (CRC) for Beef Genetic Technologies to predict P8 fat (mm) in beef cattle to assist beef producers meet...