Asymptotic behaviour of an estimator based on Rao's divergence
Asymptotic behaviour of empirical multiinformation
Asymptotic behaviour of the likelihood ratio test under presence of deviations of the model
Asymptotic behaviour of the probability-weighted moments and penultimate approximation
The P.O.T. (Peaks-Over-Threshold) approach consists of using the Generalized Pareto Distribution (GPD) to approximate the distribution of excesses over a threshold. We use the probability-weighted moments to estimate the parameters of the approximating distribution. We study the asymptotic behaviour of these estimators (in particular their asymptotic bias) and also the functional bias of the GPD as an estimate of the distribution function of the excesses. We adapt penultimate approximation results...
Asymptotic behaviour of the probability-weighted moments and penultimate approximation
The P.O.T. (Peaks-Over-Threshold) approach consists of using the Generalized Pareto Distribution (GPD) to approximate the distribution of excesses over a threshold. We use the probability-weighted moments to estimate the parameters of the approximating distribution. We study the asymptotic behaviour of these estimators (in particular their asymptotic bias) and also the functional bias of the GPD as an estimate of the distribution function of the excesses. We adapt penultimate approximation results...
Asymptotic behaviour of the quadratic measure of deviation of multivariate density estimates
Asymptotic behaviour of the robust test in the Rieder's model of contamination
Asymptotic comparison of maximum likelihood and a rank estimate in simple linear regression model
Asymptotic Considerations for Selecting the Best Component of a Multivariate Normal Population.
Asymptotic covariances for the generalized gamma distribution
The five-parameter generalized gamma distribution is one of the most flexible distributions in statistics. In this note, for the first time, we provide asymptotic covariances for the parameters using both the method of maximum likelihood and the method of moments.
Asymptotic covariances of empirical processes
Asymptotic criteria for designs in nonlinear regression with model errors
Asymptotic distribution of coordinates on high dimensional spheres.
Asymptotic distribution of Gumbel statistic in a semi-parametric approach.
Asymptotic distribution of rank statistics used for multivariate testing symmetry (Preliminary communication)
Asymptotic distribution of robust k-nearest neighbour estimator for functional nonparametric models
Asymptotic distribution of the conditional regret risk for selecting good exponential populations
In this paper empirical Bayes methods are applied to construct selection rules for the selection of all good exponential distributions. We modify the selection rule introduced and studied by Gupta and Liang [10] who proved that the regret risk converges to zero with rate . The aim of this paper is to study the asymptotic behavior of the conditional regret risk . It is shown that tends in distribution to a linear combination of independent -distributed random variables. As an application we...
Asymptotic distribution of the estimated parameters of an ARMA(p,q) process in the presence of explosive roots
We consider an autoregressive moving average process of order (p,q)(ARMA(p,q)) with stationary, white noise error variables having uniformly bounded fourth order moments. The characteristic polynomials of both the autoregressive and moving average components involve stable and explosive roots. The autoregressive parameters are estimated by using the instrumental variable technique while the moving average parameters are estimated through a derived autoregressive process using the same sample. The...
Asymptotic distribution of the likelihood ratio test statistic in the multisample case
Asymptotic Distribution of the Log-Likelihood Function for Stochastic Processes : Some Examples