In a general normal regression model, this paper first derives the least upper bound (LUB) for the covariance matrix of a generalized least squares estimator (GLSE) relative to the covariance matrix ...
Estimation for the linear model y = Xβ + e with unknown diagonal covariance matrix G is considered. The diagonal elements of G are assumed to be known functions of the explanatory variables X and an ...
In a multivariate regression model, the errors in different equations may be correlated. In this case the efficiency of the estimation may be improved by taking these cross-equation correlations into ...
In the supply and demand model, P is an endogenous variable, and consequently the OLS estimates are biased. The following example estimates this model using two-stage least squares: proc syslin ...
Download PDF More Formats on IMF eLibrary Order a Print Copy Create Citation This paper proposes a novel shrinkage estimator for high-dimensional covariance matrices by extending the Oracle ...
Abstract: The traffic matrix is a useful data structure in network management, monitoring, optimization and traffic forecast. A recurrent problem is to obtain accurate traffic matrices in real time ...
Abstract: This paper presents a novel least mean square (LMS) estimator for a sensor-less drive of a three phase induction motor. Also, the proposed system includes the use of the matrix converter ...
Linear multiplicative models are popular tools for analyzing data with positive responses. However, the linear structure of models is too restrictive on the regression relation, which may lead to a ...
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