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optimal estimate

См. также в других словарях:

  • Optimal design — This article is about the topic in the design of experiments. For the topic in optimal control theory, see shape optimization. Gustav Elfving developed the optimal design of experiments, and so minimized surveyors need for theodolite measurements …   Wikipedia

  • Stein's unbiased risk estimate — In statistics, Stein s unbiased risk estimate (SURE) is an unbiased estimator of the mean squared error of a given estimator, in a deterministic estimation scenario. In other words, it provides an indication of the accuracy of a given estimator.… …   Wikipedia

  • ball-park estimate —  A quickly calculated estimate of costs.  ► “Thus, the result obtained with a specific heuristic can be considered ‘good’ (i.e., close to optimal) if that result is in the ball park of the result obtained through a maximally different method.”… …   American business jargon

  • Kalman filter — Roles of the variables in the Kalman filter. (Larger image here) In statistics, the Kalman filter is a mathematical method named after Rudolf E. Kálmán. Its purpose is to use measurements observed over time, containing noise (random variations)… …   Wikipedia

  • Minimum mean square error — In statistics and signal processing, a minimum mean square error (MMSE) estimator describes the approach which minimizes the mean square error (MSE), which is a common measure of estimator quality. The term MMSE specifically refers to estimation… …   Wikipedia

  • Particle filter — Particle filters, also known as sequential Monte Carlo methods (SMC), are sophisticated model estimation techniques based on simulation. They are usually used to estimate Bayesian models and are the sequential ( on line ) analogue of Markov chain …   Wikipedia

  • Info-gap decision theory — is a non probabilistic decision theory that seeks to optimize robustness to failure – or opportuneness for windfall – under severe uncertainty,[1][2] in particular applying sensitivity analysis of the stability radius type[3] to perturbations in… …   Wikipedia

  • Multivariate kernel density estimation — Kernel density estimation is a nonparametric technique for density estimation i.e., estimation of probability density functions, which is one of the fundamental questions in statistics. It can be viewed as a generalisation of histogram density… …   Wikipedia

  • Kernel density estimation — of 100 normally distributed random numbers using different smoothing bandwidths. In statistics, kernel density estimation is a non parametric way of estimating the probability density function of a random variable. Kernel density estimation is a… …   Wikipedia

  • Dynamic treatment regime — In medical research, a dynamic treatment regime (DTR) or adaptive treatment strategy is a set of rules for choosing effective treatments for individual patients. The treatment choices made for a particular patient are based on that individual s… …   Wikipedia

  • Computer-adaptive testing — A computer adaptive testing (CAT) is a method for administering tests that adapts to the examinee s ability level. For this reason, it has also been called tailored testing . How CAT worksCAT successively selects questions so as to maximize the… …   Wikipedia

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