Data compression in discriminating stochastic processes
Data imputation in switchback designs using a mixed model with correlated errors.
Décomposition des processus aléatoires, une comparaison entre les méthodes factorielles et l'analyse spectrale
Degenerate limit laws for the maxima of trigonometric polynomials with random coefficients
Dependent Lindeberg central limit theorem and some applications
In this paper, a very useful lemma (in two versions) is proved: it simplifies notably the essential step to establish a Lindeberg central limit theorem for dependent processes. Then, applying this lemma to weakly dependent processes introduced in Doukhan and Louhichi (1999), a new central limit theorem is obtained for sample mean or kernel density estimator. Moreover, by using the subsampling, extensions under weaker assumptions of these central limit theorems are provided. All the usual causal...
Dependent random variables with a given marginal distribution
Detección de rasgos en imágenes binarias mediante procesos puntuales espaciales marcados.
En este trabajo consideramos el problema de la detección de rasgos bajo la presencia de ruido en imágenes que tras un cierto tratamiento se reducen a binarias, por la presencia de dos tipos de elementos. Podemos encontrar ejemplos de este problema en la detección de minas por medio de imágenes de avión o satélite, en la búsqueda de rasgos en imágenes microscópicas de células, o en la caracterización de fallas en zonas de terremotos.En primer lugar revisamos algunos métodos de detección jerárquicos...
Detecting abrupt changes in random fields
This paper is devoted to the study of some asymptotic properties of a -estimator in a framework of detection of abrupt changes in random field’s distribution. This class of problems includes e.g. recovery of sets. It involves various techniques, including -estimation method, concentration inequalities, maximal inequalities for dependent random variables and -mixing. Penalization of the criterion function when the size of the true model is unknown is performed. All the results apply under mild,...
Detecting abrupt changes in random fields
This paper is devoted to the study of some asymptotic properties of a M-estimator in a framework of detection of abrupt changes in random field's distribution. This class of problems includes e.g. recovery of sets. It involves various techniques, including M-estimation method, concentration inequalities, maximal inequalities for dependent random variables and ϕ-mixing. Penalization of the criterion function when the size of the true model is unknown is performed. All the results apply under...
Detecting Changes in a Multivariate Renewal Process.
Détection d'une rupture de moyenne en un point inconnu d'un processus ARMA
Detection of outliers and patches in bilinear time series models.
Detection of transient change in mean – a linear behavior inside epidemic interval
A procedure for testing occurrance of a transient change in mean of a sequence is suggested where inside an epidemic interval the mean is a linear function of time points. Asymptotic behavior of considered trimmed maximum-type test statistics is presented. Approximate critical values are obtained using an approximation of exceedance probabilities over a high level by Gaussian fields with a locally stationary structure.
Detekce změn v časových řadách a její aplikace v ekologii
Determination of phase-space reconstruction parameters of chaotic time series
A new method called C-C-1 method is suggested, which can improve some drawbacks of the original C-C method. Based on the theory of period N, a new quantity S(t) for estimating the delay time window of a chaotic time series is given via direct computing a time-series quantity S(m,N,r,t), from which the delay time window can be found. The optimal delay time window is taken as the first period of the chaotic time series with a local minimum of S(t). Only the first local minimum of the average of a...
Determining neighborhoods of image pixels automatically for adaptive image denoising using nonlinear time series analysis.
Development of the kriging method with application
This paper describes a modification of the kriging method for working with the square root transformation of a spatial random process. We have developed this method for the situation where the spatial process observed is not supposed to be stationary but the assumption is that its square root is a second order stationary spatial random process. Consequently this method is developed for estimating the integral of the process observed and finally some application of the method is given to data from...
Deviation inequalities and moderate deviations for estimators of parameters in an Ornstein-Uhlenbeck process with linear drift.
Deviation inequalities and moderate deviations for estimators of parameters in bifurcating autoregressive models
The purpose of this paper is to investigate the deviation inequalities and the moderate deviation principle of the least squares estimators of the unknown parameters of general th-order asymmetric bifurcating autoregressive processes, under suitable assumptions on the driven noise of the process. Our investigation relies on the moderate deviation principle for martingales.
Die Bestimmung des ARMA Modells der stationären Zeitreihe