# best linear unbiased estimator

• 1Minimum-variance unbiased estimator — In statistics a uniformly minimum variance unbiased estimator or minimum variance unbiased estimator (UMVUE or MVUE) is an unbiased estimator that has lower variance than any other unbiased estimator for all possible values of the parameter. The&#8230; …

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• 2Estimator — In statistics, an estimator is a function of the observable sample data that is used to estimate an unknown population parameter (which is called the estimand ); an estimate is the result from the actual application of the function to a&#8230; …

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• 3Linear model — In statistics the linear model is given by:Y = X eta + varepsilonwhere Y is an n times;1 column vector of random variables, X is an n times; p matrix of known (i.e. observable and non random) quantities, whose rows correspond to statistical&#8230; …

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• 4Least-squares estimation of linear regression coefficients — In parametric statistics, the least squares estimator is often used to estimate the coefficients of a linear regression. The least squares estimator optimizes a certain criterion (namely it minimizes the sum of the square of the residuals). In&#8230; …

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• 5Linear least squares (mathematics) — This article is about the mathematics that underlie curve fitting using linear least squares. For statistical regression analysis using least squares, see linear regression. For linear regression on a single variable, see simple linear regression …

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• 6BLUE — Best Linear Unbiased Estimator (Academic & Science » Ocean Science) * Baltic Latvian Universal Electronics (Academic & Science » Electronics) * United States, and it s allies (Governmental » Military) …

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• 7Least squares — The method of least squares is a standard approach to the approximate solution of overdetermined systems, i.e., sets of equations in which there are more equations than unknowns. Least squares means that the overall solution minimizes the sum of&#8230; …

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• 8Ordinary 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&#8230; …

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• 9Gauss–Markov theorem — This article is not about Gauss–Markov processes. In statistics, the Gauss–Markov theorem, named after Carl Friedrich Gauss and Andrey Markov, states that in a linear model in which the errors have expectation zero and are uncorrelated and have&#8230; …

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• 10Kriging — is a group of geostatistical techniques to interpolate the value of a random field (e.g., the elevation, z , of the landscape as a function of the geographic location) at an unobserved location from observations of its value at nearby locations.&#8230; …

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• 11Estimation theory — is a branch of statistics and signal processing that deals with estimating the values of parameters based on measured/empirical data. The parameters describe an underlying physical setting in such a way that the value of the parameters affects&#8230; …

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• 12Homoscedasticity — Plot with random data showing homoscedasticity. In statistics, a sequence or a vector of random variables is homoscedastic ( &#160; …

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• 13Point estimation — In statistics, point estimation involves the use of sample data to calculate a single value (known as a statistic) which is to serve as a best guess for an unknown (fixed or random) population parameter.More formally, it is the application of a&#8230; …

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• 14Feasible generalized least squares — (FGLS or Feasible GLS) is a regression technique. It is similar to generalized least squares except that it uses an estimated variance covariance matrix since the true matrix is not known directly.The following description follows loosely the&#8230; …

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• 15BLUP — (Abkürzung von englisch Best Linear Unbiased Prediction, auf deutsch beste lineare unverzerrte Vorhersage) ist eine statistische Methode, mit der zufällige Größen in Mehrebenenmodellen vorhergesagt werden können. Die beste lineare unverzerrte&#8230; …

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• 16Lineare Regression — Die lineare Regression ist ein Spezialfall des allgemeinen Konzepts der Regressionsanalyse, mit der versucht wird, eine abhängige Variable durch eine oder mehrere unabhängige Variablen zu erklären das Beiwort linear ergibt sich dabei daraus, dass …

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