Respondent-driven sampling is a network-based technique to collect information and make estimation about behavior and composition of social groups in hidden population. The non-randomly selected samples prohibit the use of the sample mean as a statistically valid estimator. Researchers have proposed several asymptotically unbiased estimators, but many fail to realize that the high variance of t...

In this paper, we present a new class of blind cyclic-based estimators for carrier frequency offset and symbol-timing error estimation of orthogonal frequency-division multiplexing (OFDM) systems. The proposed approach exploits the properties of the cyclic prefix subset to reveal the synchronization parameters in the likelihood function of the received vector. In this paper, a new likelihood fu...

In statistics parameter theory, usually the parameter estimations have two kinds,one is the least-square estimation(LSE),and the other is the best linear unbiased estimation (BLUE).Due to the determining theorem of minimum variance unbiased estimator(MVUE),the parameter estimation of BLUE in linear model is most ideal.But since the calculations are complicated or the covariance is not given,peo...

We propose a new unbiased estimator for estimating the utility of optimal stopping problem. The MUSE, short Multilevel Unbiased Stopping Estimator, constructs Monte Carlo (MLMC) at every stage problem in backward recursive way. In contrast to traditional sequential methods, MUSE can be implemented parallel. prove has finite variance, computational complexity, and achieves $\epsilon$-accuracy wi...

managers always consider the precise estimation of sediments in watersheds due to various conditions, such assoil and water resources management, construction, infrastructure and economical and social issues. in this condition,an optimized determination of sediment rating equation (typical method until now for sediment yield estimation) isessential to investigate sediment yield in rivers. in th...

There are some experiences that researcher come across quite number of time for very large networks in the initial samples such that they cannot finish the sampling procedure. Two solutions have been proposed and used by marine biologists which we discuss in this article: i) Adaptive cluster sampling based on order statistics with a stopping rule, ii) Restricted adaptive cluster sampling. Until...

This paper proposes a novel linear estimator named stochastic MV-PURE estimator, developed for the stochastic linear model, and designed to provide improved performance over the linear minimum mean square error (MMSE) Wiener estimator in cases prevailing in practical, real-world settings, where at least some of the second-order statistics of the random vectors under consideration are only imper...