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NIC documents and reports which are used by policymakers, include the National Intelligence Estimate and the Global Trends reports delivered every four years. The NIC's goal is to provide policymakers with the best available information, that is unvarnished, unbiased and without regard to whether the analytic judgments conform to current U.S ...
National Intelligence Estimates (NIEs) are United States federal government documents that are the authoritative assessment of the Director of National Intelligence (DNI) on intelligence related to a particular national security issue. NIEs are produced by the National Intelligence Council and express the coordinated judgments of the United ...
A standard application of SURE is to choose a parametric form for an estimator, and then optimize the values of the parameters to minimize the risk estimate. This technique has been applied in several settings. For example, a variant of the James–Stein estimator can be derived by finding the optimal shrinkage estimator. [2]
James–Stein estimator. The James–Stein estimator is a biased estimator of the mean, , of (possibly) correlated Gaussian distributed random variables with unknown means . It arose sequentially in two main published papers. The earlier version of the estimator was developed in 1956, [1] when Charles Stein reached a relatively shocking ...
Words of estimative probability (WEP or WEP s) are terms used by intelligence analysts in the production of analytic reports to convey the likelihood of a future event occurring. A well-chosen WEP gives a decision maker a clear and unambiguous estimate upon which to base a decision. Ineffective WEPs are vague or misleading about the likelihood ...
The name "S-estimators" was chosen as they are based on estimators of scale. We will consider estimators of scale defined by a function , which satisfy. R1 – is symmetric, continuously differentiable and . R2 – there exists such that is strictly increasing on. For any sample of real numbers, we define the scale estimate as the solution of.
t. e. In estimation theory and decision theory, a Bayes estimator or a Bayes action is an estimator or decision rule that minimizes the posterior expected value of a loss function (i.e., the posterior expected loss). Equivalently, it maximizes the posterior expectation of a utility function.
In statistics, the bias of an estimator (or bias function) is the difference between this estimator 's expected value and the true value of the parameter being estimated. An estimator or decision rule with zero bias is called unbiased. In statistics, "bias" is an objective property of an estimator. Bias is a distinct concept from consistency ...