Examples of using Estimator in English and their translations into Ukrainian
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As a consequence, it is no longer meaningful to speak of a Bayes estimator that minimizes the Bayes risk.
the noise statistics fed as inputs to the estimator.
some intuition about the conditions under which the difference-in-difference estimator will outperform the difference-in-mean estimator,
the non unbiased estimator of the population variance and that's denoted usually by an S squared with subscript n and what is the biased estimator?
Estimator own searches for information sources(except for documents, the disclosure of
Unfortunately, in the absence of an experiment, ignorability is not often satisfied, which means that the estimator in eq. 2.4 is not likely to produce good estimate.
some intuition about the conditions under which the difference-in-difference estimator will outperform the difference-in-mean estimator, and a simple simulation study.
a Bayes action is an estimator or decision rule that minimizes the posterior expected value of a loss function(i.e.,
the risk function of an estimator δ(x) for a parameter θ,
measure what this variable is over a bunch of hours and then average it up, and that's going to be a pretty good estimator for the actual mean of our population.
An estimator θ^{\displaystyle{\widehat{\theta}}} is said to be a Bayes estimator if it minimizes the Bayes risk among all estimators.
designer, estimator, material tester,
for the value of p using x/n, the sample proportion and estimator of p, in a common test statistic.[26].
In statistics, the delta method is a result concerning the approximate probability distribution for a function of an asymptotically normal statistical estimator from knowledge of the limiting variance of that estimator.
while the median is the estimator that minimizes expected loss experienced under the absolute-difference loss function.
Model selection techniques can be considered as estimators of some physical quantity,
including a discussion of optimal allocation and difference-in-differences estimators.
Direct estimators for the first four L-moments in a finite sample of n observations are:[6].
To derive estimators for the parameters of probability distributions,
Estimators are important to customers because they help to determine whether a project will make money for a firm