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The control architecture is comprised of a Hybrid MPC controller and a reference governor which consists of a estimator and a optimizer.
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In estimating the confidence interval the variance of an estimator must first be estimated.
Bootstrapping is widely used (e.g. in phylogenetic reconstruction [ 18]) for estimating properties of an estimator.
The bootstrap is a statistical technique for estimating the accuracy of an estimator and is available in many commonly used statistical software packages.
Figure 1a is a conventional independent detection and estimation system that consists of an estimator and a detector.
Bootstrapping is a highly computer-intensive statistical procedure for estimating the sampling distribution of an estimator by sampling with replacement from the original sample.
The root-mean-squared error (rmse) is a measure of the average "closeness" of an estimator to the value that is being estimated; smaller values of the rmse correspond to "better" estimators.
In robust estimation theory, two important concepts characterize the robustness of an estimator: the breakdown point and the influence function.
The accuracy of an estimator can be measured with the squared Euclidean distance between the estimated, θ ^, and the true value of the parameter, θ.
Mind you, faced with questions such as "What are the desirable statistical properties of an estimator?", they can hardly be blamed for that.
The RMS error of an estimator is defined as (24).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com