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- In [[statistics]], '''Whittle likelihood''' is an approximation to the [[likelihood function]] of a stationary Gaussian [[time series]]. It is named after the ...or3-first=D. L.|title=Encyclopedia of Statistical Sciences|chapter=Whittle likelihood|pages=708–710|volume=Update Volume 2|publisher=Wiley & Sons|place=New York| ...10 KB (1,464 words) - 09:35, 25 November 2024
- ...ection|selecting]] a [[statistical model]] for given data, the '''relative likelihood''' compares the relative plausibilities of different candidate models or of ==Relative likelihood of parameter values== ...6 KB (861 words) - 17:33, 2 January 2025
- ...paper.<ref>{{Cite journal|last=Owen|first=Art B.|date=1988|title=Empirical likelihood ratio confidence intervals for a single functional|url=http://dx.doi.org/10 Then, the empirical likelihood is:<ref><math>\frac{\hat{F}(y_i)-\hat{F}(y_i-\delta y)}{\delta y}</math> is ...9 KB (1,357 words) - 00:43, 12 November 2024
- ...ents given a query. This is interpreted as being the [[Likelihood function|likelihood]] of a document being relevant given a query. ==Calculating the likelihood== ...3 KB (536 words) - 18:05, 23 January 2023
- '''Maximum likelihood sequence estimation''' ('''MLSE''') is a [[mathematical algorithm]] that ex ...um likelihood sequence estimation is formally the application of [[maximum likelihood]] to this problem. That is, the estimate of {''x''(''t'')} is defined to be ...5 KB (669 words) - 19:04, 19 July 2024
- ...pecific task. From such analyses measures can then be taken to reduce the likelihood of errors occurring within a system and therefore lead to an improvement in ...mance e.g. available task time. Such factors are used to derive a Success Likelihood Index (SLI), a form of preference index, which is calibrated against existi ...16 KB (2,528 words) - 18:45, 18 December 2023
- '''Noise-Predictive Maximum-Likelihood (NPML)''' is a class of [[Signal processing|digital signal-processing]] me ...esponse maximum-likelihood]] (PRML), and extended partial-response maximum likelihood (EPRML) detection.<ref name="Eleftheriou">{{cite journal|last=Eleftheriou|f ...19 KB (2,653 words) - 18:22, 24 July 2023
- ...for [[panel data]] is a [[Quasi-maximum likelihood estimate|quasi-maximum likelihood]] method for [[panel analysis]] that assumes that density of <math>y_{it}</ ...the joint conditional distribution. This generality facilitates [[maximum likelihood]] methods in panel data setting because fully specifying conditional distri ...7 KB (1,077 words) - 13:18, 27 June 2024
Page text matches
- ...ection|selecting]] a [[statistical model]] for given data, the '''relative likelihood''' compares the relative plausibilities of different candidate models or of ==Relative likelihood of parameter values== ...6 KB (861 words) - 17:33, 2 January 2025
- ...ents given a query. This is interpreted as being the [[Likelihood function|likelihood]] of a document being relevant given a query. ==Calculating the likelihood== ...3 KB (536 words) - 18:05, 23 January 2023
- ...seph Felsenstein| title = Evolutionary trees from DNA sequences: A maximum likelihood approach | doi = 10.1007/BF01734359 | journal = Journal of Molecular Evolut ...a hypothesis test for whether evolutionary rates are constant (by using [[likelihood ratio test]]s). It can also be used to provide error estimates for the par ...5 KB (827 words) - 16:27, 4 October 2024
- '''Maximum likelihood sequence estimation''' ('''MLSE''') is a [[mathematical algorithm]] that ex ...um likelihood sequence estimation is formally the application of [[maximum likelihood]] to this problem. That is, the estimate of {''x''(''t'')} is defined to be ...5 KB (669 words) - 19:04, 19 July 2024
- ...ns and a generative model with parameters <math>\theta</math> for which no likelihood function can easily be provided. Since a maximum likelihood estimation cannot be performed, indirect inference proposes to fit a (possi ...3 KB (380 words) - 14:38, 26 January 2025
- ...of the [[gradient]], or as a function of the [[Hessian matrix]] of the log-likelihood function. ...a & \sigma^2 \end{bmatrix}</math>, the resulting [[Likelihood function|log-likelihood function]] is ...4 KB (572 words) - 09:26, 19 March 2023
- ...tiple targets. There exist several automated TMA methods such as: Maximum Likelihood Estimator (MLE), etc. === Maximum Likelihood Estimator (MLE) === ...3 KB (513 words) - 18:05, 10 December 2021
- ...paper.<ref>{{Cite journal|last=Owen|first=Art B.|date=1988|title=Empirical likelihood ratio confidence intervals for a single functional|url=http://dx.doi.org/10 Then, the empirical likelihood is:<ref><math>\frac{\hat{F}(y_i)-\hat{F}(y_i-\delta y)}{\delta y}</math> is ...9 KB (1,357 words) - 00:43, 12 November 2024
- Now, suppose its [[maximum likelihood estimator]] (MLE) <math> \hat {\beta}_{u} </math> has an asymptotic distr ...is more convenient to use the [[Score test (LM test)]]. Denote the maximum likelihood estimator under the restricted model as <math> (\hat {\beta}_{r}) </math> a ...5 KB (845 words) - 17:40, 15 January 2024
- ...[[Bayesian statistics]], where it is applied if the [[Likelihood function|likelihood]] function is not tractable (see example below). where <math>p_\theta</math> denotes the likelihood function, <math>p</math> is the [[Prior distribution|prior]] and <math>p(y) ...7 KB (1,115 words) - 07:18, 28 March 2024
- ...ref> Hausman, Hall, and Griliches then use Andersen's conditional Maximum Likelihood methodology to estimate ''b<sub>0</sub>''. Using ''n''<sub>''i''</sub> = Σ ...<ref>Andersen, E. B. (1970): "Asymptotic Properties of Conditional Maximum Likelihood Estimators." ''Journal of the Royal Statistical Society'', Series B, 32, pp ...4 KB (551 words) - 11:25, 12 February 2024
- ...is a type of [[big O in probability notation]]. In other words, the local likelihood ratio must [[convergence in distribution|converge in distribution]] to a no ...''X<sub>i</sub>'' has density function {{nowrap|''f''(''x'', ''θ'')}}. The likelihood function of the model is equal to ...5 KB (824 words) - 19:07, 27 December 2023
- These probabilities provide the building blocks for setting up the [[Likelihood function]], which ends up being:<ref>Cameron A. C. and P. K. Trivedi (2005) ...etric models]], piece-wise-constant proportional hazard models, or partial likelihood approaches that estimate the baseline hazard as a nuisance function.<ref>Wo ...4 KB (536 words) - 18:45, 25 July 2024
- ...for [[panel data]] is a [[Quasi-maximum likelihood estimate|quasi-maximum likelihood]] method for [[panel analysis]] that assumes that density of <math>y_{it}</ ...the joint conditional distribution. This generality facilitates [[maximum likelihood]] methods in panel data setting because fully specifying conditional distri ...7 KB (1,077 words) - 13:18, 27 June 2024
- ...b{R}^p</math> the values of the corresponding predictors. We then take the likelihood of one observation to be ...>th stratum. The parameters in this model can be estimated using [[maximum likelihood estimation]]. ...9 KB (1,351 words) - 13:01, 18 May 2024
- ...ining the prior density <math>\widehat{f}(\alpha_{t+1}|Y_t)</math> and the likelihood <math>f(y_{t+1}|\alpha_{t+1})</math>, the empirical filtering density can b ...{i=1}^R\omega_i},\omega_j=f(y|\alpha^j)</math>. The weights represent the likelihood function <math>f(y_{t+1}|\alpha_{t+1})</math>. ...9 KB (1,509 words) - 12:33, 9 January 2025
- A maximum likelihood estimation can be applied: ...th> for each <math>x_i</math> are known, the [[Log-likelihood function|log likelihood function]] can be simplified as below: ...6 KB (1,081 words) - 18:21, 7 February 2025
- ...journal |last=Berkson |first=Joseph |title=Minimum Chi-Square, Not Maximum Likelihood! |journal=[[Annals of Statistics]] |year=1980 |volume=8 |issue=3 |pages=457 ...hypothesis is true. However, that is not in general the case when maximum-likelihood estimation is used. It is however true asymptotically when minimum chi-squ ...4 KB (617 words) - 16:02, 31 August 2024
- ...CQAAQBAJ&dq=Does+the+Nelson%E2%80%93Aalen+estimator+construct+an+empirical+likelihood%3F&pg=PA7</ref> ...4 KB (509 words) - 22:26, 3 February 2024
- In [[statistics]], '''Whittle likelihood''' is an approximation to the [[likelihood function]] of a stationary Gaussian [[time series]]. It is named after the ...or3-first=D. L.|title=Encyclopedia of Statistical Sciences|chapter=Whittle likelihood|pages=708–710|volume=Update Volume 2|publisher=Wiley & Sons|place=New York| ...10 KB (1,464 words) - 09:35, 25 November 2024