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second Akaike criterion

См. также в других словарях:

  • Akaike information criterion — Akaike s information criterion, developed by Hirotsugu Akaike under the name of an information criterion (AIC) in 1971 and proposed in Akaike (1974), is a measure of the goodness of fit of an estimated statistical model. It is grounded in the… …   Wikipedia

  • Akaike Information Criterion — Ein Informationskriterium ist ein Kriterium zur Auswahl eines Modells in der angewandten Statistik bzw. der Ökonometrie. Dabei gehen die Anpassungsgüte des geschätzten Modells an die vorliegenden empirischen Daten (Stichprobe) und Komplexität des …   Deutsch Wikipedia

  • Ordinary least squares — This article is about the statistical properties of unweighted linear regression analysis. For more general regression analysis, see regression analysis. For linear regression on a single variable, see simple linear regression. For the… …   Wikipedia

  • Informationskriterium — Ein Informationskriterium ist ein Kriterium zur Auswahl eines Modells in der angewandten Statistik bzw. der Ökonometrie. Dabei gehen die Anpassungsgüte des geschätzten Modells an die vorliegenden empirischen Daten (Stichprobe) und Komplexität des …   Deutsch Wikipedia

  • Occam's razor — For the aerial theatre company, see Ockham s Razor Theatre Company. It is possible to describe the other planets in the solar system as revolving around the Earth, but that explanation is unnecessarily complex compared to the modern consensus… …   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

  • Determining the number of clusters in a data set — Determining the number of clusters in a data set, a quantity often labeled k as in the k means algorithm, is a frequent problem in data clustering, and is a distinct issue from the process of actually solving the clustering problem. For a certain …   Wikipedia

  • Computational phylogenetics — is the application of computational algorithms, methods and programs to phylogenetic analyses. The goal is to assemble a phylogenetic tree representing a hypothesis about the evolutionary ancestry of a set of genes, species, or other taxa. For… …   Wikipedia

  • Deviance (statistics) — In statistics, deviance is a quality of fit statistic for a model that is often used for statistical hypothesis testing. The deviance for a model M0 is defined as Here denotes the fitted values of the parameters in the model M0, while denotes the …   Wikipedia

  • Kullback–Leibler divergence — In probability theory and information theory, the Kullback–Leibler divergence[1][2][3] (also information divergence, information gain, relative entropy, or KLIC) is a non symmetric measure of the difference between two probability distributions P …   Wikipedia

  • Structural equation modeling — (SEM) is a statistical technique for testing and estimating causal relations using a combination of statistical data and qualitative causal assumptions. This definition of SEM was articulated by the geneticist Sewall Wright (1921),[1] the… …   Wikipedia

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