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Classical estimation techniques for linear models either are inconsistent, or perform somewhat poorly under stable error densities; most of them are not even rate-optimal. In this paper, we develop an original R-estimation method and investigate its asymptotic performances under stable...
Persistent link: https://www.econbiz.de/10013136793
Let I1, I2, . . . , In be a sequence of independent indicator functions de- fined on a probability space (Ω, A, P ). We say that index k is a success time if Ik = 1. The sequence I1, I2, . . . , In is observed sequentially. The objective of this article is to predict the l-th last success, if...
Persistent link: https://www.econbiz.de/10015220736
This paper is devoted to the R-estimation problem for the parameter of a stationary ARMA model. The asymptotic uniform linearity of a suitable vector of rank statistics leads to the asymptotic normality of √n-consistent R-estimates resulting from the minimization of the norm of this vector. By...
Persistent link: https://www.econbiz.de/10015220737
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Aiming at analyzing multimodal or nonconvexly supported distributions through data depth, we introduce a local extension of depth. Our construction is obtained by conditioning the distribution to appropriate depth-based neighborhoods and has the advantages, among others, of maintaining...
Persistent link: https://www.econbiz.de/10010971125
We consider the problem of detecting unobserved heterogeneity, that is, the problem of testing the absence of random individual effects in an n×T panel. We establish a local asymptotic normality property–with respect to intercept, regression coefficient, the scale parameter σ of the error,...
Persistent link: https://www.econbiz.de/10011052340
A procedure relying on linear programming techniques is developed to compute (regression) quantile regions that have been defined recently. In the location case, this procedure allows for computing halfspace depth regions even beyond dimension two. The corresponding algorithm is described in...
Persistent link: https://www.econbiz.de/10011056415
The minimum covariance determinant (MCD) estimator of scatter is one of the most famous robust procedures for multivariate scatter. Despite the quite important research activity related to this estimator, culminating in the recent thorough asymptotic study of Cator and Lopuhaä (2010, 2012), no...
Persistent link: https://www.econbiz.de/10011041923