In this paper, a modified estimation algorithm has been developed refers to covariance shaping least square estimation based on the quantum mechanical concepts and constraints. The algorithm has been applied to the speech signal and the performance is estimated using probability theories. The same models can be applied with additive white Gaussian Noise which estimates the bias in the parameter...

In this paper, a modified estimation algorithm has been developed refers to Covariance Shaping Least Square (CSLS) estimation based on the quantum mechanical concepts and constraints. The algorithm has been applied to Auto Regressive Moving Average (ARMA models with various parameter values. The same models can be applied with Colored Noise which estimates the bias in the parameter and the vali...

A variety of shrinkage methods have been proposed for estimation of some unknown parameter by considering estimators based on a prior guess of the value of the parameter. We compare some of the shrunken estimators for the parameters)! and 6 of the exponential distribution through simulation. INTRODUCTION In the estimation of an unknown parameter there often exists some form of prior knowledge a...

It has been shown that local linear smoothing possesses a variety of very attractive properties, not least being its mean square performance. However, such results typically refer only to asymptotic mean squared error, meaning the mean squared error of the asymptotic distribution, and in fact, the actual mean squared error is often in®nite. See Seifert and Gasser (1996). This diculty may be ov...

In the last decade, the renaissance of interest in discriminant analysis has been primarily motivated by possible applications to tumor classification using highdimensional microarray-based data. In this thesis, we do three things: 1. First, we introduce a new regularizing covariance estimation procedure we refer to as SHIP: SHrinking and Incorporating Prior knowledge. The resulting covariance ...