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  2. Likelihood function - Wikipedia

    en.wikipedia.org/wiki/Likelihood_function

    The log-likelihood function being plotted is used in the computation of the score (the gradient of the log-likelihood) and Fisher information (the curvature of the log-likelihood). Thus, the graph has a direct interpretation in the context of maximum likelihood estimation and likelihood-ratio tests.

  3. Likelihood-ratio test - Wikipedia

    en.wikipedia.org/wiki/Likelihood-ratio_test

    The likelihood-ratio test, also known as Wilks test, [2] is the oldest of the three classical approaches to hypothesis testing, together with the Lagrange multiplier test and the Wald test. [3] In fact, the latter two can be conceptualized as approximations to the likelihood-ratio test, and are asymptotically equivalent.

  4. Log-linear analysis - Wikipedia

    en.wikipedia.org/wiki/Log-linear_analysis

    Log-linear analysis is a technique used in statistics to examine the relationship between more than two categorical variables. The technique is used for both hypothesis testing and model building. In both these uses, models are tested to find the most parsimonious (i.e., least complex) model that best accounts for the variance in the observed ...

  5. G-test - Wikipedia

    en.wikipedia.org/wiki/G-test

    The commonly used chi-squared tests for goodness of fit to a distribution and for independence in contingency tables are in fact approximations of the log-likelihood ratio on which the G-tests are based. [4] The general formula for Pearson's chi-squared test statistic is

  6. Vuong's closeness test - Wikipedia

    en.wikipedia.org/wiki/Vuong's_closeness_test

    The numerator is the difference between the maximum likelihoods of the two models, corrected for the number of coefficients analogous to the BIC, the term in the denominator of the expression for Z, , is defined by setting equal to either the mean of the squares of the pointwise log-likelihood ratios , or to the sample variance of these values ...

  7. Logistic regression - Wikipedia

    en.wikipedia.org/wiki/Logistic_regression

    The log-likelihood that a particular set of K measurements or data points will be generated by the above probabilities can now be calculated. Indexing each measurement by k , let the k -th set of measured explanatory variables be denoted by x k {\displaystyle {\boldsymbol {x}}_{k}} and their categorical outcomes be denoted by y k {\displaystyle ...

  8. 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 ...

  9. Conditional logistic regression - Wikipedia

    en.wikipedia.org/wiki/Conditional_logistic...

    In fact, it can be shown that the unconditional analysis of matched pair data results in an estimate of the odds ratio which is the square of the correct, conditional one. [ 2 ] In addition to tests based on logistic regression, several other tests existed before conditional logistic regression for matched data as shown in related tests .