Results 221 to 230 of about 12,224 (267)

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.
openaire   +1 more source

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
openaire   +1 more source

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
openaire   +2 more sources

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.
openaire   +1 more source

Least Squares Formulation of State Estimation

IFAC Proceedings Volumes, 1994
Abstract A general formulation of least squares estimation for dynamic systems is given. An algorithm with a fixed-size estimation window and constraints on states, disturbances, and measurement noise is developed through a probabilistic interpretation of least squares estimation. Specific issues relevant to linear and nonlinear systems are discussed
DOUGLAS ROBERTSON, JAY H. LEE
openaire   +1 more source

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
openaire   +2 more sources

Is this the least squares estimate?

Biometrika, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +1 more source

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 ...
openaire   +1 more source

SUBSAMPLING LEAST SQUARES AND ELEMENTAL ESTIMATION

2018 IEEE Data Science Workshop (DSW), 2018
In large-scale regression problems where the dimension of the predictors $p$ and number of observations n are large, subsampling is sometimes used to approximate least squares estimates. One approach to this is algorithmic leveraging, which draws a subsample of size $m$ ≪ $n$ from the observations where high leverage observations (according to the ...
openaire   +1 more source

A neural network least-square estimator

1990 IJCNN International Joint Conference on Neural Networks, 1990
Problems in which the arguments of objective functions are real numbers are considered. Based on the concept of the Hopfield network, a neural network that solves the least-square estimation problem is derived. With this network, the objective function can converge to any inner point of a hypercube, giving a real-valued solution with very great speed ...
Kegin Gao, M. Omair Ahmad, M. N. Srikanta Swamy   +2 more
openaire   +1 more source