Weighted Least Squares (WLS)
Resurrecting weighted least squares
... abandon weighted least squares, but to consider alternative inference methods that offer improved higher-order asymptotic accuracy (and thus translate to improved finite-sample ...
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Weighted least squares and adaptive least squares: further empirical evidence
... using weighted least squares (WLS), also in conjunction with HC standard ...adaptive least squares (ALS), where it is ‘decided’ from the data whether the applied researcher should use ...
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Study of State Estimation Using Weighted Least Squares Method
... describes weighted least squares state estimation method and investigates how the efficiency of WLS state estimation changes according to 4 ...
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Asymptotic properties of weighted least squares estimation in weak parma models
... 7 Conclusion In this work, we have established under mild assumptions, the almost sure consistency and the asymp- totic normality of the weighted least squares estimators for invertible and causal ...
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Distributed weighted least-squares estimation with fast convergence for large-scale systems
... In this paper we study distributed static estimation for a large-scale system consisting of a network of interconnected sub- systems. Each sub-system is concerned with a subset of the un- known parameters and has ...
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Particle Swarm Optimization and Differentiation Evolution –Based Weighted Least Squares State Estimation
... the Weighted Least Squares (WLS) State Estimation ...based Weighted Least Squares State Estimation Problem for IEEE 14 and IEEE 30 bus ...
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On the Equivalence of the Weighted Least Squares and the Generalised Least Squares Estimators, with Applications to Kernel Smoothing
... Abstract The paper establishes the conditions under which the generalised least squares estima- tor of the regression parameters is equivalent to the weighted least squares estimator. ...
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On the Equivalence of the Weighted Least Squares and the Generalised Least Squares Estimators, with Applications to Kernel Smoothing
... Abstract The paper establishes the conditions under which the generalised least squares estima- tor of the regression parameters is equivalent to the weighted least squares estimator. ...
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Weighted Majorization Algorithms for Weighted Least Squares Decomposition Models
... any weighted least-squares model with differential nonnegative weights for every ...row weighted quadratic majorizing function such as (17) can be easily ...The weighted algorithm will ...
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A Comparison Of Ordinary Least Squares, Weighted Least Squares, And Other Procedures When Testing For The Equality Of Regression
... ordinary least squares (OLS) estimation, extant research has shown that the standard F performs poorly when the critical assumption of homoscedasticity is violated, resulting in increased Type I error rates ...
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Weighted Least Squares for a Nearly Perfect Min Max Fit
... the least squares poly- nomial approximation is repeated as weight in a second, now weighted, least squares approximation, then this new, second, approximation is nearly perfect in the ...
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MATHICSE Technical Report : Multilevel weighted least squares polynomial approximation
... The remainder of this paper is structured as follows. In Section 2, we review the theoretical analysis of weighted least squares approximation. In Section 3, we discuss different sampling strategies. ...
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An extension of RSS-based model comparison tests for weighted least squares
... ordinary least squares to weighted least squares through a change of variables designed to account for a heteroscedastic error ...
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Exact optimal designs for weighted least squares analysis with correlated errors
... for weighted least squares estimation in the common linear and quadratic regression model with correlated ...by weighted least ...
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Asymptotic Properties of the Weighted Least Squares Estimator Under Moments Restriction
... 1 Introduction The aim of this work is to review the paper by Hellerstein & Imbens (1982) focusing on the use of auxiliary data and a formal derivation of the asymptotic properties of the underlying Weighted ...
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EQUITY VERSUS EXCELLENCE IN ORGANIZATIONS: A SUBSTANTIVELY WEIGHTED LEAST SQUARES ANALYSIS*
... studentized residuals are calculated; these are essentially measures of how well agencies perform given the inputs (the independent variables) of the agency. SWLS weights those cases with a studentized residual greater ...
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A weighted least squares solution for space intersection of spaceborne stereo SAR data
... A Weighted Least Squares Solution for Space Intersection of Spaceborne Stereo SAR Data Pu-Huai Chen and Ian ...a weighted space inter- section algorithm based on an analysis of the predicted ...
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Derivative Estimation Based on Difference Sequence via Locally Weighted Least Squares Regression
... locally weighted least ...locally weighted least squares regression, the empirical first derivative is our special case: local constant ...locally weighted least ...
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A new approach called Weighted Least Squares Ratio (WLSR) Method to M-estimators
... Outliers– Least squares ratio (LSR) method – Weighted least squares ratio (WLSR) method – Robust statistics – ...to least squares estimation in the presence of outliers ...
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The Method of Least Squares
... the least square method is widely used to find or es- timate the numerical values of the parameters to fit a function to a set of data and to characterize the statistical properties of esti- ...ordinary ...
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