least squares estimator

least squares es·ti·ma·tor

the prescription "Assign to the unknown parameter the value that minimizes the mean of the squares of the residual errors."
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They recommended the SCAD penalty which enjoys the oracle property (a variable selection and estimation procedure is said to have the oracle property if it selects the true model A, with probability tending to one, and if the estimated coefficients are asymptotically normal, with the same asymptotic variance as the least squares estimator based on the true model) for variable selection.
The inclusion of lagged dependent variable in the list of explanatory variables introduces the specific estimation problems even the generalized least squares estimator for the dynamic panel data models allowing cross sectional heteroscedasticity becomes biased and inconsistent.
The least squares estimator and the maximum-likelihood estimator are widely used in propagation model-based localization problems.
In addition, a confirmatory factor analysis was run on MPLUS using a weighted least squares estimator (WLSMV) with categorical variables (Muthen & Muthen, 2010).
In fact, a single sufficiently deviating data point can cause that the least squares estimator breaks down and generates results that are utterly unreliable and uninformative.
Key words: Ordinary least squares estimator, best linear unbiased estimator, orthogonal projections.
The underestimation is about 54% for the Least Squares estimator for the smallest binwidth.
Adjustment results with the Least Squares estimator, Huber estimator, [L.
v] of the AR model, the least squares estimator of the AR coefficient matrices [A.
Heteroskedastic and autoregressive consistent estimates for the multiple regression procedure and the univariate probit procedure, respectively, are obtained through the use of the Fuller-Battese random effects generalized least squares estimator and the Butler-Moffit random effects maximum likelihood estimator.
For the cross-sectional censored regression model, we calculate three estimators: Powell's (1984) censored least absolute deviations estimator, Powell's (1986) symmetrically censored least squares estimator, and Honore and Powell's (1994) pairwise difference estimator.
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