Sentence examples for almost efficient estimator from inspiring English sources

In particular, our numerical results demonstrated that Tyler's estimator is an "almost" efficient estimator w.r.t. the CCRB and its estimation accuracy is independent on the value of the shape parameter.

Based on the numerical analysis, we observe that: Regarding the scatter matrix estimation, the robust C-Tyler estimator is an "almost" efficient estimator, even if it is not the most efficient estimator for t-distributed data, in fact when λ increases, the other two estimators achieve better performance.

In this scenario, since the FB is the ML estimator, then it is, at least asymptotically, the most efficient estimator.

Let us assume that the Q-range estimates are obtained independently using an efficient estimator.

The test involves comparison of results from an efficient estimator (ie, lower sample-to-sample variation in estimates) that does not correct for possible endogeneity of program exposure (random effects is such an estimator) with a less efficient estimator that does correct for the potential endogeneity of program exposure (fixed effects is the classic choice in the longitudinal data setting).

The test evaluates the consistency of an estimator when compared to an alternative, less efficient, estimator which is already known to be consistent.

Under this assumption, we obtain a large class of semiparametric estimators that extends standard inverse-probability weighting (IPW) and includes multiply robust estimators, including a locally semiparametric efficient estimator.

The results show that the maximum likelihood estimator can achieve the lower bound on the variance of the time of flight estimator and hence it is an efficient estimator.

To leverage prognostic information in baseline variables and short-term outcomes, we use a semiparametric, locally efficient estimator, and investigate its strengths and limitations compared to standard estimators.

Note that under weak conditions, the ML estimator is asymptotically an unbiased and efficient estimator [27].

Empirically relevant numerical examples illustrate that the proposed efficient estimator provides nontrivial improvement over alternatives in the extant literature.