The truncated least squares method for a class of autoregressive models.
Theoretical and numerical comparison of some sampling methods for molecular dynamics
The purpose of the present article is to compare different phase-space sampling methods, such as purely stochastic methods (Rejection method, Metropolized independence sampler, Importance Sampling), stochastically perturbed Molecular Dynamics methods (Hybrid Monte Carlo, Langevin Dynamics, Biased Random Walk), and purely deterministic methods (Nosé-Hoover chains, Nosé-Poincaré and Recursive Multiple Thermostats (RMT) methods). After recalling some theoretical convergence properties for the...
Three Digit Accurate Multiple Normal Probabilities.
Time splitting for wave equations in random media
Numerical simulation of high frequency waves in highly heterogeneous media is a challenging problem. Resolving the fine structure of the wave field typically requires extremely small time steps and spatial meshes. We show that capturing macroscopic quantities of the wave field, such as the wave energy density, is achievable with much coarser discretizations. We obtain such a result using a time splitting algorithm that solves separately and successively propagation and scattering in the simplified...
Time splitting for wave equations in random media
Numerical simulation of high frequency waves in highly heterogeneous media is a challenging problem. Resolving the fine structure of the wave field typically requires extremely small time steps and spatial meshes. We show that capturing macroscopic quantities of the wave field, such as the wave energy density, is achievable with much coarser discretizations. We obtain such a result using a time splitting algorithm that solves separately and successively propagation and scattering in the...
Towards effective dynamics in complex systems by Markov kernel approximation
Many complex systems occurring in various application share the property that the underlying Markov process remains in certain regions of the state space for long times, and that transitions between such metastable sets occur only rarely. Often the dynamics within each metastable set is of minor importance, but the transitions between these sets are crucial for the behavior and the understanding of the system. Since simulations of the original process are usually prohibitively expensive, the effective...
Tracing cluster transitions for different cluster types
Trend to equilibrium and particle approximation for a weakly selfconsistent Vlasov-Fokker-Planck equation
We consider a Vlasov-Fokker-Planck equation governing the evolution of the density of interacting and diffusive matter in the space of positions and velocities. We use a probabilistic interpretation to obtain convergence towards equilibrium in Wasserstein distance with an explicit exponential rate. We also prove a propagation of chaos property for an associated particle system, and give rates on the approximation of the solution by the particle system. Finally, a transportation inequality...
Tumour angiogenesis model with variable vessels' effectiveness
We propose a model of vascular tumour growth, which generalises the well recognised model formulated by Hahnfeldt et al. in 1999. Our model is based on the same idea that the carrying capacity for any solid tumour depends on its vessel density but it also incorporates vasculature quality which may be lost during angiogenesis as recognised by Jain in 2005. In the model we assume that the loss of vessel quality affects the diffusion coefficient inside the tumour. We analyse basic mathematical properties...
Un algorithme de calcul de la probabilité qu'une variable de Fisher-Snedecor, à premier degré de liberté impair, excède une valeur donnée
Un algoritmo iterativo para la estimación de modelos ARMA con ausencia de observaciones.
En el presente artículo se muestra un algoritmo iterativo para la estimación de parámetros de modelos ARMA en series temporales que tengan alguna observación ausente. Posteriormente se efectúa la demostración de la convergencia de dicho algoritmo. Se presenta un ejemplo de estimación basado en la simulación de series temporales con un ordenador y se exponen las conclusiones llevadas a cabo por el autor.
Un calcul probabiliste en génie civil. Évaluation de la probabilité de ruine des structures par une méthode de Monte-Carlo fondée sur une technique de conditionnement
Un método para la simulación de funciones aleatorias estacionarias de segundo orden.
A method is shown for the simulation in Rn of second order stationary random functions with given isotropic covariance. Particular solutions, ilustrated with examples, are provided in R1, R2 and R3.
Uncertainty of the design and covariance matrices in linear statistical model
The aim of the paper is to determine an influence of uncertainties in design and covariance matrices on estimators in linear regression model.
Underparametrization of weakly nonlinear regression models
A large number of parameters in regression models can be serious obstacle for processing and interpretation of experimental data. One way how to overcome it is an elimination of some parameters. In some cases it need not deteriorate statistical properties of estimators of useful parameters and can help to interpret them. The problem is to find conditions which enable us to decide whether such favourable situation occurs.
Une méthode de discrétisation de variables continues
Uniformly convergent adaptive methods for a class of parametric operator equations∗
We derive and analyze adaptive solvers for boundary value problems in which the differential operator depends affinely on a sequence of parameters. These methods converge uniformly in the parameters and provide an upper bound for the maximal error. Numerical computations indicate that they are more efficient than similar methods that control the error in a mean square sense.
Uniformly convergent adaptive methods for a class of parametric operator equations∗
We derive and analyze adaptive solvers for boundary value problems in which the differential operator depends affinely on a sequence of parameters. These methods converge uniformly in the parameters and provide an upper bound for the maximal error. Numerical computations indicate that they are more efficient than similar methods that control the error in a mean square sense.
Uniqueness of the level two Bayesian network representing a probability distribution.
Unit root testing in the presence of innovation variance breaks: a simple solution with increased power.