Sentence examples for more efficient estimator from inspiring English sources

These simulations allowed us to select the best method of calculation, obtaining quantitative estimates with acceptable accuracy (comparison with the original simulated landscapes: R2 ranging from 0.986 to 0.997); they also showed that MSA is a more efficient estimator than LIT, generating percentage coverage estimates that are less variable.

The Hausman test suggests that it is safe to use random effects, which offer a more efficient estimator.

A more efficient estimator of the data variance should be based on the asymptotic variance formula for the location M estimate in (28).

In terms of within-limb sampling strategies, this study provides clear evidence that a systematic sample along a limb gives a more efficient estimator of mean FW compared with random or stratified sampling.

Although we do not require this assumption to use our estimators for the relationship matrices, it does suggest that a more efficient estimator might be chosen by appropriately weighting each term in the summations for Φ ^ m and Δ ^ m, with the optimal weights depending upon both how IBS at a marker captures IBD at a polygene and the relative magnitude of the variance at that polygene.

Simultaneous regression techniques lead to more efficient estimators.

Obtaining more efficient estimators in the presence of contemporaneous correlated errors across units and heteroskedasticity in panel data models.

It is shown that our approach proposed, compared to the maximum likelihood estimator, the least squares estimator, and the weighted least squares estimator, yields more efficient estimators.

We have shown that in reality, this bound on acceleration does not hold, which justifies the search for better and more efficient estimators.

We argued that this approach provided more efficient estimators than cross-sectional designs, given the same number and pattern of observations, and allowed exclusion of between-subject variation from model error.

Of the two methods, it is believed that the log-binomial regression yields more efficient estimators because it is maximum likelihood based, while the robust Poisson model may be less affected by outliers.