Here you will find one or more explanations in English for the word **Likelihood**. Also in the bottom left of the page several parts of wikipedia pages related to the word **Likelihood** and, of course, **Likelihood** synonyms and on the right images related to the word **Likelihood**.

Likelihood

Likelihood Like"li*hood (-l[i^]*h[oo^]d), n. [Likely + -hood.] 1. Appearance; show; sign; expression. [Obs.] What of his heart perceive you in his face By any likelihood he showed to-day ? --Shak. 2. Likeness; resemblance. [Obs.] There is no likelihood between pure light and black darkness, or between righteousness and reprobation. --Sir W. Raleigh. 3. Appearance of truth or reality; probability; verisimilitude. --Tennyson.

Likelihood Like"li*hood (-l[i^]*h[oo^]d), n. [Likely + -hood.] 1. Appearance; show; sign; expression. [Obs.] What of his heart perceive you in his face By any likelihood he showed to-day ? --Shak. 2. Likeness; resemblance. [Obs.] There is no likelihood between pure light and black darkness, or between righteousness and reprobation. --Sir W. Raleigh. 3. Appearance of truth or reality; probability; verisimilitude. --Tennyson.

- a likelihood function (often simply the likelihood) is a function of the parameters of a statistical model, given specific observed data. Likelihood functions...

- In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of a statistical model, given observations. MLE attempts to...

- In statistics, a likelihood ratio test (LR test) is a statistical test used for comparing the goodness of fit of two statistical models — a null model...

- (LR+, likelihood ratio positive, likelihood ratio for positive results) and negative likelihood ratio (LR–, likelihood ratio negative, likelihood ratio...

- Likelihood ratio may refer to: The ratio of two likelihood functions Likelihood-ratio test, a statistical test for comparing two models Likelihood ratios...

- In statistics, a marginal likelihood function, or integrated likelihood, is a likelihood function in which some parameter variables have been marginalized...

- The elaboration likelihood model (ELM) of persuasion is a dual process theory describing the change of attitudes. The ELM was developed by Richard E. Petty...

- In statistics, quasi-likelihood estimation is one way of allowing for overdispersion, that is, greater variability in the data than would be expected from...

- expectation–maximization (EM) algorithm is an iterative method to find maximum likelihood or maximum a posteriori (MAP) estimates of parameters in statistical models...

- the likelihood principle is that, given a statistical model, all the evidence in a sample relevant to model parameters is contained in the likelihood function...

- In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of a statistical model, given observations. MLE attempts to...

- In statistics, a likelihood ratio test (LR test) is a statistical test used for comparing the goodness of fit of two statistical models — a null model...

- (LR+, likelihood ratio positive, likelihood ratio for positive results) and negative likelihood ratio (LR–, likelihood ratio negative, likelihood ratio...

- Likelihood ratio may refer to: The ratio of two likelihood functions Likelihood-ratio test, a statistical test for comparing two models Likelihood ratios...

- In statistics, a marginal likelihood function, or integrated likelihood, is a likelihood function in which some parameter variables have been marginalized...

- The elaboration likelihood model (ELM) of persuasion is a dual process theory describing the change of attitudes. The ELM was developed by Richard E. Petty...

- In statistics, quasi-likelihood estimation is one way of allowing for overdispersion, that is, greater variability in the data than would be expected from...

- expectation–maximization (EM) algorithm is an iterative method to find maximum likelihood or maximum a posteriori (MAP) estimates of parameters in statistical models...

- the likelihood principle is that, given a statistical model, all the evidence in a sample relevant to model parameters is contained in the likelihood function...

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