efficient estimator

efficient estimator

[ə¦fish·ənt ′es·tə‚mād·ər]
(statistics)
A statistical estimator that has minimum variance.
References in periodicals archive ?
1] is designated to be the more efficient estimator.
However, Coal is efficient estimator then other energy resources.
The general consensus of opinion, however, is that, thus far, two-stage least squares is the cheapest, easiest, and most efficient estimator in most situations [24].
This latter work takes advantage of a GMM efficient estimator for dynamic panels.
Regarding specific goals, it is necessary to establish efficient criteria to select the optimal lag-length (parametric), as well as the approach of an efficient estimator of the long-run variance (semi-parametric).
As a consequence, an estimator that provides a non-optimal solution close to the correct value is preferred instead of a much efficient estimator that provides an absurd solution when any assumption does not fulfil.
It should be noted that since the overidentifying restrictions of the model are not rejected, we could, in principle, combine the various estimators for the change in the black-white earnings gap into a more efficient estimator.
Overall, the geometric average is the most efficient estimator, and the overlapping average is the least efficient.
The sample 10 percent trimmed mean is clearly the most efficient estimator, with an RMSE that is more than 15 percent below that of the sample mean, with a 30 percent lower variance
Three versions of each model (zero lag, geometric lag, and almon lag) are estimated using, in each case, an efficient estimator.
The quantile regression estimator described above is not an efficient estimator for [[Beta].
The proposal is divided into three research projects whose goals are: (1) Obtain upper and lower bounds for the density of the solution to the two types of SPDEs (i) and (ii), by means of the Malliavin Calculus; (2) Use these bounds in order to prove the local asymptotic normality (LAN) for the models (i) and (ii), and then apply Hajek-Lecam~s theorem to obtain asymptotically efficient estimators for the parameter of the equations; (3) Study Monte Carlo methods and exact simulation of the SDE model with jumps (i), and apply these computational methods to the following financial problems: jump volatility models and numerical computations of greeks.
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