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(modified maximum likelihood estimate)

См. также в других словарях:

  • 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

  • Maximum parsimony — Maximum parsimony, often simply referred to as parsimony, is a non parametric statistical method commonly used in computational phylogenetics for estimating phylogenies. Under maximum parsimony, the preferred phylogenetic tree is the tree that… …   Wikipedia

  • Maximum parsimony (phylogenetics) — Parsimony is a non parametric statistical method commonly used in computational phylogenetics for estimating phylogenies. Under parsimony, the preferred phylogenetic tree is the tree that requires the least evolutionary change to explain some… …   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

  • Climate sensitivity — is a measure of how responsive the temperature of the climate system is to a change in the radiative forcing. It is usually expressed as the temperature change associated with a doubling of the concentration of carbon dioxide in Earth s… …   Wikipedia

  • Sensibilidad climática — Uno o varios wikipedistas están trabajando actualmente en este artículo o sección. Es posible que a causa de ello haya lagunas de contenido o deficiencias de formato. Si quieres, puedes ayudar y editar, pero por favor: antes de realizar… …   Wikipedia Español

  • Least absolute deviations — (LAD), also known as Least Absolute Errors (LAE), Least Absolute Value (LAV), or the L1 norm problem, is a mathematical optimization technique similar to the popular least squares technique that attempts to find a function which closely… …   Wikipedia

  • Scale-inverse-chi-square distribution — Probability distribution name =Scale inverse chi square type =density pdf cdf parameters = u > 0, sigma^2 > 0, support =x in (0, infty) pdf =frac{(sigma^2 u/2)^{ u/2{Gamma( u/2)} frac{expleft [ frac{ u sigma^2}{2 x} ight] }{x^{1+ u/2 cdf… …   Wikipedia

  • von Mises distribution — von Mises Probability density function The support is chosen to be [ π,π] with μ=0 Cumulative distribution function The support is chosen to be [ π,π] with μ=0 …   Wikipedia

  • Standard deviation — In probability and statistics, the standard deviation is a measure of the dispersion of a collection of values. It can apply to a probability distribution, a random variable, a population or a data set. The standard deviation is usually denoted… …   Wikipedia

  • Iterative proportional fitting — The iterative proportional fitting procedure (IPFP, also known as biproportional fitting in statistics, RAS algorithm[1] in economics and matrix raking or matrix scaling in computer science) is an iterative algorithm for estimating cell values of …   Wikipedia

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