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marginal vector

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  • Copula (probability theory) — In probability theory and statistics, a copula can be used to describe the dependence between random variables. Copulas derive their name from linguistics. The cumulative distribution function of a random vector can be written in terms of… …   Wikipedia

  • Multivariate normal distribution — MVN redirects here. For the airport with that IATA code, see Mount Vernon Airport. Probability density function Many samples from a multivariate (bivariate) Gaussian distribution centered at (1,3) with a standard deviation of 3 in roughly the… …   Wikipedia

  • Dirichlet distribution — Several images of the probability density of the Dirichlet distribution when K=3 for various parameter vectors α. Clockwise from top left: α=(6, 2, 2), (3, 7, 5), (6, 2, 6), (2, 3, 4). In probability and… …   Wikipedia

  • Gibbs sampling — In statistics and in statistical physics, Gibbs sampling or a Gibbs sampler is an algorithm to generate a sequence of samples from the joint probability distribution of two or more random variables. The purpose of such a sequence is to… …   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

  • Microeconomía — El modelo de oferta y demanda describe como varían los precios según el balance entre disponibilidad del producto a diferentes precios (oferta) y los deseos de aquellos con poder adquisitivo según el precio (demanda). La gráfica muestra un… …   Wikipedia Español

  • Luigi Pasinetti — «Pasinetti» redirige aquí. Para otras acepciones, véase Pasinetti (desambiguación). Luigi Pasinetti. Luigi L. Pasinetti (12 de Septiembre de 1930) es un economista italiano de la escuela de economía postkeynesiana. Pasinetti es considerado el… …   Wikipedia Español

  • Supervised learning — is a machine learning technique for learning a function from training data. The training data consist of pairs of input objects (typically vectors), and desired outputs. The output of the functioncan be a continuous value (called regression), or… …   Wikipedia

  • Glossary of probability and statistics — The following is a glossary of terms. It is not intended to be all inclusive. Concerned fields *Probability theory *Algebra of random variables (linear algebra) *Statistics *Measure theory *Estimation theory Glossary *Atomic event : another name… …   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

  • Belief propagation — is a message passing algorithm for performing inference on graphical models, such as Bayesian networks and Markov random fields. It calculates the marginal distribution for each unobserved node, conditional on any observed nodes. Belief… …   Wikipedia

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