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This paper revisits the classical inference results for profile quasi maximum likelihood estimators (profile MLE) in the semiparametric estimation problem. We mainly focus on two prominent theorems: t...
PReMiuM is a recently developed R package for Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, non-parametrically linking a response vect...
The main focus of this work is on developing models for the ac-tivity profile of a terrorist group, detecting sudden spurtsand down-falls in this profile, and in general, tracking it over a period of ...
It is very important to consider and to be aware of the profile of community health workers in order to provide appropriate alternatives when working with these groups as well as with the indigenous p...
Companies must have resources that provide competitive advantages and are important factors for success. There is a great variety of such resources—including information systems, concepts of participa...
We examine the spectral profile bound of Goel, Montenegro and Tetali - for the L mixing time of continuous-time random walk in reversible settings. We find that it is precise up to a loglog factor, an...
The principal objective of the study was to determine the personality profile of police recruits who are high on anxiety. A secondary objective was to determine whether there are gender and ethnic dif...
We show that for all p>p_c(Z^d) percolation parameters, the probability that the cluster of the origin is finite but has at least t vertices at distance one from the infinite cluster is exponentially ...
The generalized varying coefficient partially linear model with growing number of predictors arises in many contemporary scientific endeavor. In this paper we set foot on both theoretical and practi...
We propose an easy-to-use methodology to allocate one of the groups which have been previously built from a complete learning data base, to new individuals. The learning data base contains continuou...
The penalized profile sampler for semiparametric inference is an extension of the profile sampler method [8] obtained by profiling a penalized log-likelihood. The idea is to base inference on the po...

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