The most appealing feature of FA as potential estimator of stress and fitness is that a biologically complex and poorly understood property (i.e. DS) can be estimated by simply measuring both sides of a bilaterally symmetric trait.
Another potential estimator is the nonparametric maximum likelihood estimator (NPMLE) [ 2, 3], which is often used to analyze interval-censored data.
To assess the performance of the proposed and other potential estimators, we derive an unconditional Cramér Rao bound (CRB) which, similarly to the proposed blind channel estimator, does not assume the knowledge of the transmitted information symbols.
Successively refined economic potential estimators serve as the driving force for systematically advancing the design effort.
Two potential estimators for mean restricted time total costs (C i total) in the face of censored data are the full-sample and uncensored case estimators. 1, 9, 13 In the full-sample estimator, the accumulated cost for each participant is averaged, irrespective of whether the patient died, was observed for the full follow-up period, or was censored.
A potential application of this estimator is the dynamic correction of beamforming errors in medical imaging that result from discrepancy between the assumed and actual biological tissue velocities.
If our sole interest was to measure an "average treatment effect" (ATE), then we could easily introduce a treatment indicator with corresponding coefficient in α of Equation 2 or alternatively use a standard potential outcomes estimator.
The order-α estimator was developed a potential solution to the known problems in other non-parametric estimators described above, and where α ∈ (0,1] corresponds to the level of an appropriate non-standard conditional quantile frontier. The choice of α is continuous on the interval (0,1].
We believe that the WC model using the superpopulation variance estimator may provide a potential alternative analytical method for case-control analyses with detailed information on the history of the exposure of interest, especially if a large part of the subjects has a time-varying exposure intensity over lifetime, and if only one control is available for each case.
Finally, we propose that the present methodology represents the seed of a potential tool for systematically comparing connectivity estimators.
