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conditional maximum likelihood method

См. также в других словарях:

  • Maximum likelihood — In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of a statistical model. When applied to a data set and given a statistical model, maximum likelihood estimation provides estimates for the model s… …   Wikipedia

  • Maximum likelihood sequence estimation — (MLSE) is a mathematical algorithm to extract useful data out of a noisy data stream. Contents 1 Theory 2 Background 3 References 4 Further reading …   Wikipedia

  • Likelihood function — In statistics, a likelihood function (often simply the likelihood) is a function of the parameters of a statistical model, defined as follows: the likelihood of a set of parameter values given some observed outcomes is equal to the probability of …   Wikipedia

  • Conditional random field — A conditional random field (CRF) is a statistical modelling method often applied in pattern recognition. More specifically it is a type of discriminative undirected probabilistic graphical model. It is used to encode known relationships between… …   Wikipedia

  • Likelihood principle — In statistics,the likelihood principle is a controversial principle of statistical inference which asserts that all of the information in a sample is contained in the likelihood function.A likelihood function arises from a conditional probability …   Wikipedia

  • Empirical Bayes method — In statistics, empirical Bayes methods are a class of methods which use empirical data to evaluate / approximate the conditional probability distributions that arise from Bayes theorem. These methods allow one to estimate quantities… …   Wikipedia

  • Monotone likelihood ratio — A monotonic likelihood ratio in distributions f(x) and g(x) The ratio of the density functions above is increasing in the parameter x, so f(x)/g(x) satisfies the monotone likelihood ratio property. In statistics, the monoto …   Wikipedia

  • Expectation-maximization algorithm — An expectation maximization (EM) algorithm is used in statistics for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. EM alternates between performing an… …   Wikipedia

  • Linear regression — Example of simple linear regression, which has one independent variable In statistics, linear regression is an approach to modeling the relationship between a scalar variable y and one or more explanatory variables denoted X. The case of one… …   Wikipedia

  • Confidence interval — This article is about the confidence interval. For Confidence distribution, see Confidence Distribution. In statistics, a confidence interval (CI) is a particular kind of interval estimate of a population parameter and is used to indicate the… …   Wikipedia

  • Normal distribution — This article is about the univariate normal distribution. For normally distributed vectors, see Multivariate normal distribution. Probability density function The red line is the standard normal distribution Cumulative distribution function …   Wikipedia

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