enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. 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).

  3. Likelihood principle - Wikipedia

    en.wikipedia.org/wiki/Likelihood_principle

    For example, the result of a significance test depends on the p-value, the probability of a result as extreme or more extreme than the observation, and that probability may depend on the design of the experiment. To the extent that the likelihood principle is accepted, such methods are therefore denied.

  4. Log probability - Wikipedia

    en.wikipedia.org/wiki/Log_probability

    In probability theory and computer science, a log probability is simply a logarithm of a probability. [1] The use of log probabilities means representing probabilities on a logarithmic scale ( − ∞ , 0 ] {\displaystyle (-\infty ,0]} , instead of the standard [ 0 , 1 ] {\displaystyle [0,1]} unit interval .

  5. Wilks' theorem - Wikipedia

    en.wikipedia.org/wiki/Wilks'_theorem

    For example: If the null model has 1 parameter and a log-likelihood of −8024 and the alternative model has 3 parameters and a log-likelihood of −8012, then the probability of this difference is that of chi-squared value of (()) = with = degrees of freedom, and is equal to .

  6. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    In probability theory and statistics, a probability distribution is the mathematical function that gives the probabilities of occurrence of possible outcomes for an experiment. [1] [2] It is a mathematical description of a random phenomenon in terms of its sample space and the probabilities of events (subsets of the sample space). [3]

  7. Likelihood-ratio test - Wikipedia

    en.wikipedia.org/wiki/Likelihood-ratio_test

    In statistics, the likelihood-ratio test is a hypothesis test that involves comparing the goodness of fit of two competing statistical models, typically one found by maximization over the entire parameter space and another found after imposing some constraint, based on the ratio of their likelihoods.

  8. Statistical manifold - Wikipedia

    en.wikipedia.org/wiki/Statistical_manifold

    A simple example of a statistical manifold, taken from physics, would be the canonical ensemble: it is a one-dimensional manifold, with the temperature T serving as the coordinate on the manifold. For any fixed temperature T , one has a probability space: so, for a gas of atoms, it would be the probability distribution of the velocities of the ...

  9. Likelihoodist statistics - Wikipedia

    en.wikipedia.org/wiki/Likelihoodist_statistics

    Likelihoodist statistics or likelihoodism is an approach to statistics that exclusively or primarily uses the likelihood function. Likelihoodist statistics is a more minor school than the main approaches of Bayesian statistics and frequentist statistics , but has some adherents and applications.