We consider the problem of estimation the population mean of the study variate Y in presence of measurement errors when information on an auxiliary character X is known. A class of estimators for population means using information on an auxiliary variate X is defined. Expressions for its asymptotic bias and mean square error are obtained. Optimum conditions are obtained for which the mean...

Based on a single cumulant of any order M > 3, a new allpass system identification algorithm with only non-Gaussian output measurements is proposed in this paper. The proposed algorithm, which includes both parameter estimation and order determination of linear time-invariant (LTI) allpass systems, outperforms other cumulant based methods such as least-squares estimators simply due to the more ...

reservoir permeability is a critical parameter for characterization of the hydrocarbon reservoirs. in fact, determination of permeability is a crucial task in reserve estimation, production and development. traditional methods for permeability prediction are well log and core data analysis which are very expensive and time-consuming. well log data is an alternative approach for prediction of pe...

In this paper, adaptive discrete-time low-gain integral control strategies are presented for tracking constant reference signals for infinite-dimensional discrete-time power-stable linear systems. The discrete-time results are applied in the development of adaptive sampled-data low-gain integral control of well-posed infinite-dimensional exponentially stable linear systems. Our results consider...

A simple targeting algorithm for trans-Earth injection is developed. The techniques presented in this paper build on techniques developed for the Apollo program and other lunar and interplanetary missions. Presently, more sophisticated algorithms exist for solving this problem, but the simplicity of this particular algorithm makes it well-suited for on-board use during contingency and abort ope...

Precise identification of the time when a process has changed enables process engineers to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for a Poisson process in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step < /div> change, a linear trend and a known multip...

We have developed the correction algorithm of the closed orbit distortion (COD) under the constraint condition where beam positions at particular points are not changed. The new algorithm is based on the modified PSINOM algorithm including the regularization process in order to avoid the inversion problem of the ill-posed response matrices. We have confirmed that the COD is well corrected with ...

Active learning refers to algorithmic frameworks aimed at selecting training data points in order to reduce the number of required training data points and/or improve the generalization performance of a learning method. In this paper, we present an asymptotic analysis of active learning for generalized linear models. Our analysis holds under the common practical situation of model misspecificat...