Results 251 to 260 of about 75,728 (293)

Asymptotic efficiency of the ordinary least-squares estimator for sur models with integrated regressors

Statistics and Probability Letters, 2007
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Dong Wan Shin
exaly   +3 more sources

Parameter estimation of a DC motor using ordinary least squares and recursive least squares algorithms

Proceedings of the 8th International Conference on Frontiers of Information Technology, 2010
This paper gives an insight into the working and efficiency of the two basic algorithms used for parameter estimation: Ordinary Least Squares (OLS) and Recursive Least Squares (RLS). A simple DC motor is taken here as an example of a SISO system. The input voltage and the output in the form of rotations of the motor are given to the parameter estimator.
Saher Arshad, Saima Qamar, Tayba Jabbar, Ahsan Malik   +3 more
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Frequency and Phase-Angle Estimation Using Ordinary Least Squares

IEEE Transactions on Industrial Electronics, 2015
The extensive use of grid-connected power electronics converters in the most different conditions, e.g., grid voltage quality, power level and grid codes, requires a robust synchronization method in order to properly feed other converter controllers with reliable and exact information, namely the phase-angle and the magnitude of the grid voltage.
Carlos João Ramos, António P. Martins 0001, Adriano S. Carvalho   +2 more
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The Existence of Moments of the Ordinary Least Squares and Two-Stage Least Squares Estimators

Econometrica, 1972
This paper deals with two single-equation estimators in a set of simultaneous linear stochastic equations--namely, ordinary least squares (OLS) and two-stage least squares (2SLS). Under the assumption that all predetermined variables in the model are exogenous, necessary and sufficient conditions are obtained for the existence of even moments of the ...
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Ordinary and weighted least-squares estimators

Canadian Journal of Statistics, 1990
Summary: We propose a method of estimating the asymptotic relative efficiency (ARE) of the weighted least-squares estimator (WLSE) with respect to the ordinary least-squares estimator (OLSE) in a heteroscedastic linear regression model with a large number of observations but a small number of replicates at each value of the regressors. The weights used
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On the Asymptotic Bias of the Ordinary Least Squares Estimator of the Tobit Model

Econometrica, 1981
This paper presents a precise characterization of the bias of least squares in two limited dependent variable models, the Tobit model and the truncated regression model. For the cases considered, the method of moments can be used to correct the bias of OLS. For more general cases, the results provide approximations which appear to be relatively robust.
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A COMPARISON OF ORDINARY LEAST SQUARES AND LEAST ABSOLUTE ERROR ESTIMATION

1986
In a linear dynamic model with heteroscedastic errors, we compare some aspects of ordinary least squares and least absolute error estimation. After deriving the properties of the estimators and the Wald, Lagrange multiplier and Likelihood ratio tests under a local alternative, we derive the Hausman test comparing the estimators.
Weiss, Andrew, Weiss, Andrew
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ASYMPTOTIC EFFICIENCY OF THE ORDINARY LEAST SQUARES ESTIMATOR FOR REGRESSIONS WITH UNSTABLE REGRESSORS

Econometric Theory, 2002
For regression models with general unstable regressors having characteristic roots on the unit circle and general stationary errors independent of the regressors, sufficient conditions are investigated under which the ordinary least squares estimator (OLSE) is asymptotically efficient in that it has the same limiting distribution as the ...
Shin, Dong Wan, Oh, Man Suk
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On the invalidity of the ordinary least squares estimate of the equilibrium climate sensitivity

Theoretical and Applied Climatology, 2021
The equilibrium climate sensitivity is often estimated by the ordinary least squares applied to annual data of observed/calculated temperature and forcing series. One of the conditions under which the ordinary least squares estimator is consistent is the uncorrelatedness of the regressor and regression error.
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Ordinary Least Squares Estimation for a Dynamic Game [PDF]

, 2014
Estimation of dynamic games is known to be a numerically challenging task. A common form of the payoff functions employed in practice takes the linear-in-parameter specification. We show a least squares estimator taking a familiar OLS/GLS expression is available in such case. Our proposed estimator has a closed-form.
Fabio A. Miessi Sanches, Daniel Silva Junior, Sorawoot Srisuma   +1 more
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