… estimate back on track. We use the Stochastic Learning Weak Estimator (SLWE) as the
dynamic estimator. … Therefore, the SLWE is a better choice to accompany a stationary estimator …

… the MA and AR parameter estimators are the same under weak identification. The uniform …
of lack of identification or weak identification on the behavior of the extremum estimator ̂θn In …

… GEL estimators are first-order equivalent under weak identification+ The GEL estimator under
weak … of the GMM and GEL parameter estimates under weak identification ~established in …

… It is worth noting that the update rule developed in this paper enables the use of weak
estimators to classify data not only into more than two classes, but also data with nonbinary …

… of estimator, we simply mean some algorithm which maps our data set to an estimate of d. …
the most conventional and straightforward estimator. Because the noise has zero mean, this …

… importantly on the choice of estimator, because some esti… estimator, denoted by ̂βB2SLS
n.In general, not all members of the k-class of estimators are equally robust to instrument weak…

… Weak constraint parameter estimation is applied to tune a 0-D 4-component (phytoplankton, …
, we employed weak constraint parameter estimation. It is worth noting that, as a rule, weak …

… out precisely when parameters are estimated which affect the … of estimators but, in general,
these appear to be rather weak. … do not restrict the type of estimator (labeled upper bound and …

… parameter for finite sample bias becomes even more pronounced when we consider the
absolute bias of the IV estimator, relative to that of the OLS estimator as defined by …

… robust parameter estimation based on a certain cross entropy and divergence. The robust
estimate is … Let θ ˆ be the estimator of the parameter θ based on the observations x 1 , … , x n …