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  2. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    The log-normal distribution is the maximum entropy probability ... the log-likelihood ... p1 and p2, for RR), and we wish to calculate their ratio. ...

  3. Likelihood function - Wikipedia

    en.wikipedia.org/wiki/Likelihood_function

    The χ 2 distribution given by Wilks' theorem converts the region's log-likelihood differences into the "confidence" that the population's "true" parameter set lies inside. The art of choosing the fixed log-likelihood difference is to make the confidence acceptably high while keeping the region acceptably small (narrow range of estimates).

  4. Log probability - Wikipedia

    en.wikipedia.org/wiki/Log_probability

    Similarly, likelihoods are often transformed to the log scale, and the corresponding log-likelihood can be interpreted as the degree to which an event supports a statistical model. The log probability is widely used in implementations of computations with probability, and is studied as a concept in its own right in some applications of ...

  5. Maximum likelihood estimation - Wikipedia

    en.wikipedia.org/wiki/Maximum_likelihood_estimation

    In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed data.This is achieved by maximizing a likelihood function so that, under the assumed statistical model, the observed data is most probable.

  6. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    The log-likelihood of a normal variable is simply the log of its probability density function: ⁡ = ⁡ (). Since this is a scaled and shifted square of a standard normal variable, it is distributed as a scaled and shifted chi-squared variable.

  7. Multivariate normal distribution - Wikipedia

    en.wikipedia.org/wiki/Multivariate_normal...

    Since the log likelihood of a normal vector is a quadratic form of the normal vector, it is distributed as a generalized chi-squared variable. [ 17 ] Differential entropy

  8. Likelihood-ratio test - Wikipedia

    en.wikipedia.org/wiki/Likelihood-ratio_test

    Many common test statistics are tests for nested models and can be phrased as log-likelihood ratios or approximations thereof: e.g. the Z-test, the F-test, the G-test, and Pearson's chi-squared test; for an illustration with the one-sample t-test, see below.

  9. Wilks' theorem - Wikipedia

    en.wikipedia.org/wiki/Wilks'_theorem

    In statistics, Wilks' theorem offers an asymptotic distribution of the log-likelihood ratio statistic, which can be used to produce confidence intervals for maximum-likelihood estimates or as a test statistic for performing the likelihood-ratio test.