Results 251 to 260 of about 2,712,723 (299)

Least squares parameter estimation

Automatica, 1979
Abstract This article demonstrates the application of least squares for the estimation of system parameters. Analytic as well as numerical approaches are described. The model of the system dynamics is assumed in the form of regression model. Solutions are discussed for the case of white noise and correlated noise corrupting the useful output signal ...
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Minimax Estimators Dominating the Least-Squares Estimator

Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2006
We present several analytical and numerical results demonstrating the superiority of minimax estimators over least-squares (LS) estimation. We show that, for any bounded parameter set, a linear minimax estimator achieves lower mean-squared error than the LS estimator, over the entire parameter set.
Zvika Ben-Haim, Yonina C. Eldar
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Constrained Least Squares Interval Estimation

SIAM Journal on Scientific and Statistical Computing, 1985
The estimation of confidence intervals is extended to the rank deficient case in least squares linear regression: \(y=Kx+e\), \(rank(K)
Pierce, Jane E., Rust, Bert W.
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Constrained Indirect Least Squares Estimators

Econometrica, 1978
An over-identified model could be defined as an exactly identified model that is subject to over-identifying restrictions. One could therefore define a constrained indirect least squares estimator for systems of equations similar to generalized least squares estimators under constraints for single equations. The estimator differs from three stage least
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On Computing the Least Quantile of Squares Estimate

SIAM Journal on Scientific Computing, 1998
Summary: In linear regression, an important role is played by the least quantile of squares (LQS) estimate, which involves the minimization of the qth smallest squared residual for a given set of data. This function is nondifferentiable and nonconvex and may have a large number of local minima.
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A Least-Squares Strain Estimator for Elastography

Ultrasonic Imaging, 1997
A least-squares strain estimator (LSQSE) for elastography is proposed. It is shown that with such an estimator, the signal-to-noise ratio in an elastogram ( SNR e ) is significantly improved. This improvement is illustrated theoretically using a modified strain filter and experimentally using
F, Kallel, J, Ophir
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Is this the least squares estimate?

Biometrika, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Partially Generalized Least Squares and Two-Stage Least Squares Estimators

Journal of Econometrics, 1983
Abstract A class of partially generalized least squares estimators and a class of partially generalized two-stage least squares estimators in regression models with heteroscedastic errors are proposed. By using these estimators a researcher can attain higher efficiency than that attained by the least squares or the two-stage least squares estimators ...
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Least Squares Estimation

2018
In Chap. 1 we learned how to solve a system of linear equations. All of the systems were square (i.e., the number of equations equaled the number of unknowns) and each system had an exact solution. Systems like these do not characterize most statistical analyses.
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Least-squares estimation of enzyme parameters

Computers in Biology and Medicine, 1991
The estimation of the enzyme parameters Km and Vmax from initial velocity data, or of analogous parameters in binding or transport experiments may be accomplished by transformation of the data, or by a direct weighted least-squares fit. Although the latter makes better use of the data, the method is complex and may be sensitive to initial parameter ...
M E, Jones, K, Taransky
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