As an alternative to the local partial likelihood method of Tibshirani and Hastie and Fan, Gijbels, and King, a global partial likelihood method is proposed to estimate the covariate effect in a nonparametric proportional hazards model, λ(t|x) = exp{ψ(x)}λ(0)(t). The estimator, ψ̂(x), reduces to the Cox partial likelihood estimator if the covariate is discrete. The estimator is shown to be consi...

The presence of aerosol has resulted in serious limitations in the data coverage and large uncertainties in retrieving carbon dioxide (CO2) amounts from satellite measurements. For this reason, an aerosol retrieval algorithm was developed for the Thermal and Near-infrared Sensor for carbon Observation-Cloud and Aerosol Imager (TANSO-CAI) launched in January 2009 on board the Greenhouse Gases Ob...

In this paper a new blind deconvolution algorithm as modzjkation of the Bellini ‘s ‘Bussgang ’ is presented. Firstly, a novel version based on stochastic Gradient Steepest Descent error minimization technique isproposed. Then the Bayesian estimator used by Bellini is approximated with a flexible Sigmoid’ parameterized with adjustable amplitude and slope, and a gradient-based technique is propos...

let be a random sample from a normal distribution with unknown mean and known variance the usual estimator of the mean, i.e., sample mean is the maximum likelihood estimator which under squared error loss function is minimax and admissible estimator. in many practical situations, is known in advance to lie in an interval, say for some in this case, the maximum likelihood estimator changes and d...

The senseless (sens) gene is required for proper development of most cell types of the embryonic and adult peripheral nervous system (PNS) of Drosophila. Sens is a nuclear protein with four Zn fingers that is expressed and required in the sensory organ precursors (SOP) for proper proneural gene expression. Ectopic expression of Sens in many ectodermal cells causes induction of PNS external sens...

~. Le probl~me central de la linguistique est congu comme la construction d'un module fonctionnel (susceptible d'etre r~alis~ sous forme d'un programme pour ordinateur) du langage, c'est-~-dire, d'un syst~me qui transforme n'importe quel sens donn~ en textes correspondants ou vice-versa. Partant du fait fondamental qu'en parlant on ne fait qu'exprimer un contenu pr~congu, le module ici pr~sent~...

Abstract A recently proposed SLOPE estimator [6] has been shown to adaptively achieve the minimax $\ell _2$ estimation rate under high-dimensional sparse linear regression models [25]. Such optimality holds in regime where sparsity level $k$, sample size $n$ and dimension $p$ satisfy $k/p\rightarrow 0, k\log p/n\rightarrow 0$. In this paper, we characterize error of complementary both $k$ scale...