Search for "Likelihood" in article titles:

1. 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) [100%] 2023-09-17
2. 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) [100%] 2023-09-07 [Likelihood] [Bayesian statistics]...
3. 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 ... [100%] 2023-06-09 [Mathematics Workgroup] [Mathematics Content]...
4. Introduction to Likelihood Theory: The goal of this course is to familiarize students with the formal definition of likelihood and its properties relevant to statistics, with all the demonstrations and proofs included. Initially, there is no intention to go beyond maximum likelihood estimation and ... [70%] 2023-04-06 [Statistics] [Mathematics]...
5. Cancer Likelihood in Plasma: Cancer Likelihood in Plasma (CLiP) refers to a set of ensemble learning methods for integrating various genomic features useful for the noninvasive detection of early cancers from blood plasma. An application of this technique for early detection of lung cancer ... [70%] 2024-01-02 [Machine learning] [Machine learning algorithms]...
6. Likelihood ratios in diagnostic testing: In evidence-based medicine, likelihood ratios are used for assessing the value of performing a diagnostic test. They use the sensitivity and specificity of the test to determine whether a test result usefully changes the probability that a condition (such ... (Medicine) [63%] 2023-10-27 [Medical statistics] [Evidence-based medicine]...
7. 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 ... [100%] 2023-09-05 [Likelihood] [Statistical models]...
8. 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. [100%] 2023-10-11 [Time series] [Time series models]...
9. 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) [100%] 2023-09-05 [Probability distribution fitting]
10. 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) [100%] 2023-10-11 [Probability distribution fitting]
11. Computational likelihood physics: Computational likelihood physics: There is a lot of power in the likelihood function applied to physics using the complex likelihood derived from the complex logarithm. For theories that are equally, proportionally, discrete, or continuously likely a likelihood ratio can be ... [81%] 2023-04-01 [Physics] [Computer science]...
12. Maximum likelihood method: If measurements y have been performed, and p(y|x) is the normalized ( ) probability density of y as function of parameters x, then the parameters x can be estimated by maximizing the joint probability density for the m measurements yj ... [81%] 2022-08-20 [W.Krisher and R.Bock] [Data analysis]...
13. Likelihood-ratio test: A statistical test based on the ratio of the greatest values of the likelihood functions under the hypothesis being tested and under all possible states of nature. Let a random variable $ X $ have values in the sample space $ \{ \mathfrak X ... (Mathematics) [81%] 2023-08-24
14. Likelihood-ratio test: In statistics, the likelihood-ratio test assesses the goodness of fit of two competing statistical models, specifically one found by maximization over the entire parameter space and another found after imposing some constraint, based on the ratio of their likelihoods ... (Statistical test to compare goodness of fit) [81%] 2023-11-19 [Statistical ratios] [Statistical tests]...
15. Elaboration likelihood model: The elaboration likelihood model (ELM) of persuasion is a dual process theory describing the change of attitudes. The ELM was developed by Richard E. (Finance) [81%] 2023-12-22 [E-commerce]
16. Monotone likelihood ratio: The ratio of the density functions above is increasing in the parameter x {\displaystyle x} , so f ( x ) / g ( x ) {\displaystyle f(x)/g(x)} satisfies the monotone likelihood ratio property. In statistics, the monotone likelihood ratio property is a ... [81%] 2023-05-14 [Theory of probability distributions] [Statistical hypothesis testing]...
17. Maximum-likelihood method: One of the fundamental general methods for constructing estimators of unknown parameters in statistical estimation theory. Suppose one has, for an observation $ X $ with distribution $ {\mathsf P} _ \theta $ depending on an unknown parameter $ \theta \in \Theta \subseteq \mathbf R ... (Mathematics) [81%] 2024-01-12
18. Probabilistic likelihood model: In simple terms a probabilistic likelihood model is a mathematical model which gives the probability of some observation (data) for some stated mathematical model capable of predicting said data as an outcome (observation). It is typically denoted as p(D ... [81%] 2023-03-03 [Probability and Statistics]
19. Restricted maximum likelihood: In statistics, the restricted (or residual, or reduced) maximum likelihood (REML) approach is a particular form of maximum likelihood estimation that does not base estimates on a maximum likelihood fit of all the information, but instead uses a likelihood function ... [81%] 2023-08-01 [Maximum likelihood estimation]
20. Elaboration likelihood model: The elaboration likelihood model (ELM) of persuasion is a dual process theory describing the change of attitudes. The ELM was developed by Richard E. (Dual process theory) [81%] 2022-02-06 [Attitude change] [Advertising]...
21. Generalized quasi-likelihood: Generalized Quasi-likelihood (GQL) Inference* by Brajendra C. Sutradhar Memorial University Email address: bsutradh@mun.ca QL Estimation for Independent Data. (Mathematics) [81%] 2023-06-24 [Statprob]
22. 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. [70%] 2023-09-06 [Hydrology] [Probability assessment]...
23. 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) [70%] 2023-09-09 [Telecommunications techniques] [Error detection and correction]...
24. Quasi-maximum likelihood estimate: In statistics a quasi-maximum likelihood estimate (QMLE), also known as a pseudo-likelihood estimate or a composite likelihood estimate, is an estimate of a parameter θ in a statistical model that is formed by maximizing a function that is related ... [70%] 2023-08-20 [Maximum likelihood estimation]
25. Partial-response maximum-likelihood: In computer data storage, partial-response maximum-likelihood (PRML) is a method for recovering the digital data from the weak analog read-back signal picked up by the head of a magnetic disk drive or tape drive. PRML was introduced ... (Method for interpreting data in digital storage systems) [70%] 2023-08-16 [Computer storage devices]
26. Noise-predictive maximum-likelihood detection: Noise-Predictive Maximum-Likelihood (NPML) is a class of digital signal-processing methods suitable for magnetic data storage systems that operate at high linear recording densities. It is used for retrieval of data recorded on magnetic media. [63%] 2022-12-16 [Hard disk drives] [Digital signal processing]...
27. 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 ... [57%] 2023-09-05 [Parametric statistics]
28. Partial likelihood methods for panel data: }} Partial (pooled) likelihood estimation for panel data is a quasi-maximum likelihood method for panel analysis that assumes that density of yit given xit is correctly specified for each time period but it allows for misspecification in the conditional density ... [57%] 2023-08-08 [M-estimators] [Maximum likelihood estimation]...
29. Distribution-free maximum likelihood for binary responses: In this article, let’s take the latent utility model as an example for the binary response model. The intuition of the latent utility model is that respondents will pick up the choice which will give the highest utility for ... [53%] 2023-04-22 [Categorical regression models]