Catálogo de publicaciones - libros

In this paper, we study the asymptotic distribution of a simple two-stage (Hannan-Rissanen-type) linear estimator for stationary invertible vector autoregressive moving average (VARMA) models in the echelon form representation. General conditions for consistency and asymptotic normality are given. A consistent estimator of the asymptotic covariance matrix of the estimator is also provided, so that tests and confidence intervals can easily be constructed.

In this paper, we provide a review of some recent results for ARMA models with uncorrelated but non independent errors. The standard so-called Box-Jenkins methodology rests on the errors independence. When the errors are suspected to be non independent, which is often the case in real situations, this methodology needs to be adapted. We study in detail the main steps of this methodology in the above-mentioned framework.

The aim of this paper is to present efficient algorithms for the detection of multiple targets in noisy images. The algorithms are based on the optimal filter of a multidimensional Markov chain signal. We also present some simulations, in the case of one, two and three targets, showing the efficiency of the method for detecting the positions of the targets.

Locally asymptotically optimal tests for testing stationary against periodic AR() dependence have been constructed by Bentarzi and Hallin (1996) in the univariate setting. These tests are generalized here to the multivariate context. A local asymptotic normality property is derived for -variate -periodic VAR() models in the vicinity of the stationary ones. The central sequence and the locally optimal tests are expressed in terms of a generalized concept of residual cross-covariance matrices.

In this paper, we adapt the Wilcoxon signed-rank test to the case of cluster correlated data. A simple modification of the estimator of the asymptotic variance is sufficient to obtain a valid asymptotic procedure. However, the resulting test is no longer distribution-free. We derive the asymptotic null distribution of the statistic. A simulation study is performed in order to investigate the finite sample performance of the test. The results show that the performance of the test is very good for all designs and distributions considered when compared to competitors based on signs and on the overall average. In fact, the test is as powerful as the one based on the overall average for normal data as soon as intracluster correlation is present. An example of application with a real data set is also given.