Poissonian products of random weights: uniform convergence and related measures.
Polynômes trigonométriques et marches aléatoires multidimensionnelles : application à la théorie ergodique
Positive Matrix Functions on the Bitorus with Prescribed Fourier Coefficients in a Band.
Positive operatorwertige Maβe und banachraumwertige stationäre Prozesse auf LCA-Gruppen
Positivity of integrated random walks
Take a centered random walk and consider the sequence of its partial sums . Suppose is in the domain of normal attraction of an -stable law with . Assuming that is either right-exponential (i.e. for some and all ) or right-continuous (skip free), we prove that as , where depends on the distribution of the walk. We also consider a conditional version of this problem and study positivity of integrated discrete bridges.
Potential theory of one-dimensional geometric stable processes
The purpose of this paper is to find optimal estimates for the Green function and the Poisson kernel for a half-line and intervals of the geometric stable process with parameter α ∈ (0,2]. This process has an infinitesimal generator of the form . As an application we prove the global scale invariant Harnack inequality as well as the boundary Harnack principle.
Power spectrum of the periodic group pulse process
Power spectrum of the quasiperiodic and the aperiodic group pulse process
Power variation of multiple fractional integrals
Precise small deviations in L 2 of some Gaussian processes appearing in the regression context
We find precise small deviation asymptotics with respect to the Hilbert norm for some special Gaussian processes connected to two regression schemes studied by MacNeill and his coauthors. In addition, we also obtain precise small deviation asymptotics for the detrended Brownian motion and detrended Slepian process.
Predictable local times and exit systems
Predictable representation of martingale spaces and changes of probability measures
Predictable representation property of some Hilbertian martingales.
Predictable sets and set-valued processes
Prediction for Two Processes and the Nehari Problem.
Prediction of time series by statistical learning: general losses and fast rates
We establish rates of convergences in statistical learning for time series forecasting. Using the PAC-Bayesian approach, slow rates of convergence √ d/n for the Gibbs estimator under the absolute loss were given in a previous work [7], where n is the sample size and d the dimension of the set of predictors. Under the same weak dependence conditions, we extend this result to any convex Lipschitz loss function. We also identify a condition on the parameter space that ensures similar rates for the...
Prediction problems [Book]
Prédiction scalaire ou prédiction vectorielle pour des processus faiblement stationnaires
Prediction sequences in smooth Banach spaces
Présentation de l'«inégalité de Doob» de Métivier et Pellaumail