Search for "Estimator" in article titles:

1. Estimator: In statistics, an estimator is a rule for calculating an estimate of a given quantity based on observed data: thus the rule (the estimator), the quantity of interest (the estimand) and its result (the estimate) are distinguished. For example, the ... (Rule for calculating an estimate of a given quantity based on observed data) [100%] 2024-11-04 [Estimator]
2. Estimator: In statistics, an estimator is a rule for calculating an estimate of a given quantity based on observed data: thus the rule (the estimator), the quantity of interest (the estimand) and its result (the estimate) are distinguished. For example, the ... (Rule for calculating an estimate of a given quantity based on observed data) [100%] 2026-01-13 [Estimator]
3. Civil estimator: A Civil estimator is a construction professional who bids on civil projects that have gone to tender. Civil estimators typically have a background in civil engineering, construction project management, or construction supervision. (Engineering) [70%] 2023-12-11 [Civil engineering]
4. Efficient estimator: An unbiased statistical estimator whose variance is the lower bound in the Rao–Cramér inequality. An efficient estimator is a sufficient statistic for the parameter to be estimated. (Mathematics) [70%] 2023-10-25
5. Superefficient estimator: hyperefficient estimator An abbreviation of the phrase "superefficient sequence of estimators" , used for a consistent sequence of asymptotically-normal estimators of an unknown parameter that is better (more efficient) than a consistent sequence of maximum-likelihood estimators. Let $ X _ ... (Mathematics) [70%] 2022-12-29
6. Invariant estimator: In statistics, the concept of being an invariant estimator is a criterion that can be used to compare the properties of different estimators for the same quantity. It is a way of formalising the idea that an estimator should have ... [70%] 2023-06-18 [Estimator] [Invariant theory]...
7. Invariant estimator: In statistics, the concept of being an invariant estimator is a criterion that can be used to compare the properties of different estimators for the same quantity. It is a way of formalising the idea that an estimator should have ... [70%] 2023-02-28 [Estimator] [Invariant theory]...
8. Minimax estimator: A statistical estimator obtained as a result of the application of the notion of a minimax statistical procedure in the problem of statistical estimation. Example 1. (Mathematics) [70%] 2023-10-13
9. Ratio estimator: The ratio estimator is a statistical parameter and is defined to be the ratio of means of two random variables. Ratio estimates are biased and corrections must be made when they are used in experimental or survey work. [70%] 2022-10-09 [Statistical deviation and dispersion] [Articles containing proofs]...
10. Consistent estimator: An abbreviated form of the term "consistent sequence of estimators" , applied to a sequence of statistical estimators converging to a value being evaluated. In probability theory, there are several different notions of the concept of convergence, of which the most ... (Mathematics) [70%] 2023-10-21
11. S-estimator: The goal of S-estimators is to have a simple high-breakdown regression estimator, which share the flexibility and nice asymptotic properties of M-estimators. The name "S-estimators" was chosen as they are based on estimators of scale. [70%] 2023-04-09 [Estimator] [Robust regression]...
12. Unbiased estimator: A statistical estimator whose expectation is that of the quantity to be estimated. Suppose that in the realization of a random variable $ X $ taking values in a probability space $ ( \mathfrak X , \mathfrak B , {\mathsf P} _ \theta ) $, $ \theta \in \Theta ... (Mathematics) [70%] 2023-09-10
13. M-estimator: In statistics, M-estimators are a broad class of extremum estimators for which the objective function is a sample average. Both non-linear least squares and maximum likelihood estimation are special cases of M-estimators. (Class of statistical estimators) [70%] 2023-05-04 [M-estimators] [Estimator]...
14. Bayesian estimator: An estimator of an unknown parameter from the results of observations using the Bayesian approach. In such an approach to the problem of statistical estimation it is usually assumed that the unknown parameter $ \theta \in \Theta \subseteq \mathbf R ^ {k ... (Mathematics) [70%] 2023-05-14
15. Linear estimator: A linear function of observable random variables, used (when the actual values of the observed variables are substituted into it) as an approximate value (estimate) of an unknown parameter of the stochastic model under analysis (see Statistical estimator). The special ... (Mathematics) [70%] 2023-10-17
16. Minimax estimator: In statistical decision theory, where we are faced with the problem of estimating a deterministic parameter (vector) θ ∈ Θ {\displaystyle \theta \in \Theta } from observations x ∈ X , {\displaystyle x\in {\mathcal {X}},} an estimator (estimation rule) δ M {\displaystyle \delta ^{M}\,\!} is called ... [70%] 2022-09-22 [Decision theory] [Estimator]...
17. M-estimator: A generalization of the maximum-likelihood estimator (MLE) in mathematical statistics (cf. also Maximum-likelihood method; Statistical estimator). (Mathematics) [70%] 2023-10-17
18. Biased estimator: A statistical estimator whose expectation does not coincide with the value being estimated. Let $ X $ be a random variable taking values in a sampling space $ ( \mathfrak X , {\mathcal B} , {\mathsf P} _ \theta ) $, $ \theta \in \Theta $, and let $ T = T ... (Mathematics) [70%] 2023-09-22
19. Bayes estimator: 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 ... (Estimator or decision rule that minimizes the posterior expected value of a loss function) [70%] 2022-09-29 [Estimator] [Bayesian estimation]...
20. Point estimator: A statistical estimator whose values are points in the set of values of the quantity to be estimated. Suppose that in the realization $ x = ( x _ {1} \dots x _ {n} ) ^ {T} $ of the random vector $ X = ( X _ {1 ... (Mathematics) [70%] 2022-11-08
21. Equivariant estimator: A statistical point estimator that preserves the structure of the problem of statistical estimation relative to a given group of one-to-one transformations of a sampling space. Suppose that in the realization of a random vector $ X = ( X _ ... (Mathematics) [70%] 2022-09-15
22. Shrinkage estimator: In statistics, a shrinkage estimator is an estimator that, either explicitly or implicitly, incorporates the effects of shrinkage. In loose terms this means that a naive or raw estimate is improved by combining it with other information. [70%] 2023-05-22 [Estimator]
23. Interval estimator: for the unknown true value of a scalar parameter of a probability distribution An interval belonging to the set of admissible values of the parameters, with boundaries that are functions of the results of observations subject to the given distribution ... (Mathematics) [70%] 2023-10-18
24. Trimmed estimator: In statistics, a trimmed estimator is an estimator derived from another estimator by excluding some of the extreme values, a process called truncation. This is generally done to obtain a more robust statistic, and the extreme values are considered outliers. [70%] 2022-11-02 [Estimator] [Robust statistics]...
25. Pitman estimator: An equivariant estimator for the shift parameter with respect to a group of real shifts, having minimal risk with respect to a quadratic loss function. Let the components $ X _ {1} \dots X _ {n} $ of a random vector $ X ... (Mathematics) [70%] 2023-09-05
26. L-estimator: In statistics, an L-estimator is an estimator which is a linear combination of order statistics of the measurements (which is also called an L-statistic). This can be as little as a single point, as in the median (of ... [70%] 2023-12-14 [Nonparametric statistics] [Robust statistics]...
27. Statistical estimator: A function of random variables that can be used in estimating unknown parameters of a theoretical probability distribution. Methods of the theory of statistical estimation form the basis of the modern theory of errors; physical constants to be measured are ... (Mathematics) [70%] 2024-01-13
28. L-estimator: In statistics, an L-estimator is an estimator which is a linear combination of order statistics of the measurements (which is also called an L-statistic). This can be as little as a single point, as in the median (of ... [70%] 2024-04-01 [Nonparametric statistics] [Robust statistics]...
29. Minimax estimator: In statistical decision theory, where we are faced with the problem of estimating a deterministic parameter (vector) \displaystyle{ \theta \in \Theta }[/math] from observations \displaystyle{ x \in \mathcal{X}, }[/math] an estimator (estimation rule) \displaystyle{ \delta^M \,\! }[/math] is called ... [70%] 2024-06-27 [Decision theory] [Estimator]...
30. Adaptive estimator: In statistics, an adaptive estimator is an estimator in a parametric or semiparametric model with nuisance parameters such that the presence of these nuisance parameters does not affect efficiency of estimation. Formally, let parameter θ in a parametric model consists of ... [70%] 2024-11-03 [Estimator]