least squares

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least squares

(lēst skwārz),
A principle of estimation invented by Gauss in which the estimates of a set of parameters in a statistical model are the quantities that minimize the sum of squared differences between the observed values of the dependent variable and the values predicted by the model.
References in periodicals archive ?
From our ordinary least squares and ordered logit models multiple regression analysis, we demonstrated that technically efficient surgeons have shorter length of active clinical services at a university hospital.
Table 3: The Effect of WIC on Well-Child Visits Variables Number of WCVs Ordinary least squares (OLS) WIC participation 0.331 (***) (0.0103) Maternal fixed effects (FE) WIC participation 0.197 (***) (0.0166) Observations 290,377 Variables Probability of WCV Ordinary least squares (OLS) WIC participation 0.0251 (***) (0.00134) Maternal fixed effects (FE) WIC participation 0.0102 (***) (0.00239) Observations 290,377 Variables At Least Six WCVs Ordinary least squares (OLS) WIC participation 0.0245 (***) (0.00162) Maternal fixed effects (FE) WIC participation 0.0159 (***) (0.00278) Observations 290,377 Notes.
On the basis of the traditional regression model, the spatial lag model and spatial error model are introduced to analyze the influencing factors of divorce rate in various provinces of China, and the results are compared with those of ordinary least square regression.
The estimates for the [[beta].sub.1] parameter, which represents the asymptotic weight, were close for the ordinary least square minima (OLS) model and for the median quantile regression one (QR ([tau] = 0.5)), with masses of 23.1320g and 23.3309g, respectively.
When using the ordinary least square method and the linear regression method, the variance of the estimated coefficient is larger (Wang, 2014).
Linear regression using ordinary least squares on log-transformed data and non-linear regression were used to compare the results.
A Linear Ordinary Least Squares. Ordinary Least Squares is the optimized technology by minimizing estimated squared errors.
Such a classification is of interest both for the description of the analyzed process and for parameter estimation, since the estimation method mostly used in econometrics, the OLS (Ordinary Least Squares) method, is well-adapted only to the linear case (Ebanca, 1994).
Keywords: Linear models Ordinary least square Method Recursive Test
In a situation, where the series are cointegrated at first difference 'I(1)', Fully modified ordinary least squares (FMOLS) is suitable for estimation.
Then, we deduce the approximate form of the ordinary least squares estimators of (a, [bet]) in long-memory stochastic volatility.