We consider parameter estimation for linear stochastic differential equations with independent experiments observed at infrequent and irregularly spaced follow-up times. The maximum likelihood method is used to obtain an asymptotically consistent estimator. A kernel-weighted score function proposed the in drift terms. strong consistency rate of convergence estimator are obtained. numerical resu...

This paper is devoted to the localization of magnetoacoustic sources moving in a straight line at a constant speed. Our technique is based on the association of narrow band acoustic signals and magnetostatic measurements. First of all, we describe features that make possible the association of magnetic and acoustic data, secondly, we show that positioning accuracy is much improved by this assoc...

We consider a simple through-the-origin linear regression example introduced by Rousseeuw, van Aelst and Hubert (1999). It is shown that the conventional least squares and least absolute error estimators converge in distribution without normalization and consequently are inconsistent. A class of weighted median regression estimators, including the maximum depth estimator of Rousseeuw and Hubert...

Abstract: We present theoretical properties of the log-concave maximum likelihood estimator of a density based on an independent and identically distributed sample in R. Our study covers both the case where the true underlying density is log-concave, and where this model is misspecified. We begin by showing that for a sequence of log-concave densities, convergence in distribution implies much s...

A new generalization of the exponential distribution, namely generalized mixture is introduced. Some its basic properties, such as hazard function, moments, order statistics, mean deviation, measures uncertainly, and reliability probability, are studied. Three different estimation methods investigated by maximum likelihood estimator, least-square weighted estimator. The performances estimators ...