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1. Generalised likelihood uncertainty estimation: Generalized likelihood uncertainty estimation (GLUE) is a statistical method used in hydrology for quantifying the uncertainty of model predictions. The method was introduced by Keith Beven and Andrew Binley in 1992. [100%] 2023-09-06 [Hydrology] [Probability assessment]...
2. Maximum likelihood sequence estimation: Maximum likelihood sequence estimation (MLSE) is a mathematical algorithm to extract useful data out of a noisy data stream. For an optimized detector for digital signals the priority is not to reconstruct the transmitter signal, but it should do a ... (Algorithm for analyzing noisy data streams) [100%] 2023-09-09 [Telecommunications techniques] [Error detection and correction]...
3. Estimation: This learning resource is about methods for estimation As main challenge is the limitation of testing capabilities. Estimation (or estimating) is the process of finding an estimate, or approximation, which is a value that is usable for some purpose even ... [96%] 2023-09-08 [Mathematical Modelling] [Statistics]...
4. Estimation: Estimation (or estimating) is the process of finding an estimate or approximation, which is a value that is usable for some purpose even if input data may be incomplete, uncertain, or unstable. The value is nonetheless usable because it is ... (Process of finding an approximation) [96%] 2024-08-22 [Estimation theory]
5. Maximum likelihood estimation with flow data: Maximum likelihood estimation with flow data is a parametric approach to deal with flow sampling data. Assume that we have observations of ai the time a person enters the state of interest, some observables xi, and the censoring of the ... [81%] 2023-09-05 [Parametric statistics]
6. 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) [75%] 2024-11-04 [Estimator]
7. 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) [75%] 2026-01-13 [Estimator]
8. Likelihood equation: An equation obtained by the maximum-likelihood method when finding statistical estimators of unknown parameters. Let $X$ be a random vector for which the probability density $p(x|\theta)$ contains an unknown parameter $\theta \in \Theta$. (Mathematics) [72%] 2023-09-17
9. Relative likelihood: In statistics, suppose that we have been given some data, and we are selecting a statistical model for that data. The relative likelihood compares the relative plausibilities of different candidate models or of different values of a parameter of a ... [72%] 2023-09-05 [Likelihood] [Statistical models]...
10. Whittle likelihood: In statistics, Whittle likelihood is an approximation to the likelihood function of a stationary Gaussian time series. It is named after the mathematician and statistician Peter Whittle, who introduced it in his PhD thesis in 1951. [72%] 2023-10-11 [Time series] [Time series models]...
11. Likelihood function: The likelihood function (often simply called the likelihood) is the joint probability of the observed data viewed as a function of the parameters of a statistical model. In maximum likelihood estimation, the arg max (over \displaystyle{ \theta }[/math]) of the ... (Function related to statistics and probability theory) [72%] 2023-09-07 [Likelihood] [Bayesian statistics]...
12. Empirical likelihood: In probability theory and statistics, empirical likelihood (EL) is a nonparametric method for estimating the parameters of statistical models. It requires fewer assumptions about the error distribution while retaining some of the merits in likelihood-based inference. (Method of estimating statistical parameters) [72%] 2023-09-05 [Probability distribution fitting]
13. Empirical likelihood: In probability theory and statistics, empirical likelihood (EL) is a nonparametric method for estimating the parameters of statistical models. It requires fewer assumptions about the error distribution while retaining some of the merits in likelihood-based inference. (Method of estimating statistical parameters) [72%] 2023-10-11 [Probability distribution fitting]
14. Likelihood ratio: In diagnostic tests, the likelihood ratio is the likelihood that a clinical sign is in a patient with disease as compared to a patient without disease. To calculate probabilities of disease using a likelihood ratio: This is a form of ... [72%] 2023-06-09 [Mathematics Workgroup] [Mathematics Content]...
15. Statistical estimation: One of the fundamental parts of mathematical statistics, dedicated to the estimation using random observations of various characteristics of their distribution. Let $ X _ {1} \dots X _ {n} $ be independent random variables (or observations) with a common unknown distribution ... (Mathematics) [68%] 2024-01-12
16. Estimation lemma: In mathematics the estimation lemma, also known as the ML inequality, gives an upper bound for a contour integral. If f is a complex-valued, continuous function on the contour Γ and if its absolute value |f (z)| is bounded by ... [68%] 2023-09-06 [Theorems in complex analysis]
17. Estimation theory: Estimation theory is a branch of statistics that deals with estimating the values of parameters based on measured empirical data that has a random component. The parameters describe an underlying physical setting in such a way that their value affects ... (Branch of statistics to estimate models based on measured data) [68%] 2023-09-08 [Estimation theory] [Signal processing]...
18. Concurrent estimation: In discrete event simulation concurrent estimation is a technique used to estimate the effect of alternate parameter settings on a discrete event system. For example from observation of a (computer simulated) telecommunications system with a specified buffer size \displaystyle{ B_0 ... [68%] 2024-01-10 [Control theory] [Events (computing)]...
19. Estimate; Estimation: ESTIMATE; ESTIMATION es'-ti-mat, es-ti-ma'-shun (`arakh, `erekh): These words, meaning "to set in order," "valuation," are used in connection with the priestly services in Leviticus 5:15,18; 6:6; 27:14, and frequently; Numbers 18 ... [68%] 1915-01-01
20. Parameter estimation: In probability, once a model class has been selected it is then necessary to estimate the values of its associated parameters in order to specify that particular model out of all members of the model class which differ only on ... [68%] 2023-06-30 [Probability and Statistics]