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There is a page named "Covariance group" on Wikipedia

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  • Thumbnail for Covariance group
    In physics, a covariance group is a group of coordinate transformations between frames of reference (see for example Ryckman (2005)). A frame of reference...
    3 KB (311 words) - 02:01, 25 July 2023
  • Covariance in probability theory and statistics is a measure of the joint variability of two random variables. The sign of the covariance, therefore,...
    29 KB (4,693 words) - 08:43, 18 June 2024
  • Thumbnail for Covariance matrix
    and statistics, a covariance matrix (also known as auto-covariance matrix, dispersion matrix, variance matrix, or variance–covariance matrix) is a square...
    34 KB (5,418 words) - 23:44, 30 May 2024
  • Thumbnail for Poincaré group
    The Poincaré group, named after Henri Poincaré (1906), was first defined by Hermann Minkowski (1908) as the isometry group of Minkowski spacetime. It...
    15 KB (2,165 words) - 19:11, 14 May 2024
  • Analysis of covariance (ANCOVA) is a general linear model that blends ANOVA and regression. ANCOVA evaluates whether the means of a dependent variable...
    10 KB (1,357 words) - 06:43, 20 December 2023
  • group of coordinate transformations between admissible frames of reference of the physical theory. This group is referred to as the covariance group....
    4 KB (471 words) - 01:47, 13 March 2024
  • In theoretical physics, general covariance, also known as diffeomorphism covariance or general invariance, consists of the invariance of the form of physical...
    6 KB (657 words) - 00:01, 23 May 2024
  • statistics, sometimes the covariance matrix of a multivariate random variable is not known but has to be estimated. Estimation of covariance matrices then deals...
    25 KB (3,930 words) - 18:26, 13 June 2024
  • through space". Lorentz covariance, a related concept, is a property of the underlying spacetime manifold. Lorentz covariance has two distinct, but closely...
    21 KB (2,917 words) - 02:30, 14 May 2024
  • together, and may refer to: Covariance matrix, a matrix of covariances between a number of variables Covariance or cross-covariance between two random variables...
    2 KB (285 words) - 12:08, 16 November 2019
  • Multivariate analysis of covariance (MANCOVA) is an extension of analysis of covariance (ANCOVA) methods to cover cases where there is more than one dependent...
    7 KB (930 words) - 12:27, 4 August 2023
  • Thumbnail for Pearson correlation coefficient
    the covariance of two variables and the product of their standard deviations; thus, it is essentially a normalized measurement of the covariance, such...
    57 KB (8,223 words) - 04:15, 2 June 2024
  • Thumbnail for Principal component analysis
    eigenvectors of the data's covariance matrix. Thus, the principal components are often computed by eigendecomposition of the data covariance matrix or singular...
    114 KB (14,283 words) - 16:28, 14 June 2024
  • discipline or warmth, are moderately heritable. Television viewing, peer group orientations and social attitudes have all been shown to be moderately heritable...
    13 KB (1,669 words) - 09:09, 5 January 2024
  • vectors in general are covariant since they can be pushed forward. See also Covariance and contravariance of vectors. Every functor F : C → D {\displaystyle...
    24 KB (3,336 words) - 07:27, 6 June 2024
  • Thumbnail for Linear discriminant analysis
    that the class covariances are identical, so Σ 0 = Σ 1 = Σ {\displaystyle \Sigma _{0}=\Sigma _{1}=\Sigma } ) and that the covariances have full rank....
    46 KB (5,950 words) - 07:10, 23 May 2024
  • representations of the general covariance group. However, there are of course spinorial representations of the Lorentz group. This fact is utilized by employing...
    15 KB (2,949 words) - 01:17, 12 February 2024
  • Thumbnail for Variance
    average value. It is the second central moment of a distribution, and the covariance of the random variable with itself, and it is often represented by σ 2...
    57 KB (10,006 words) - 05:28, 11 June 2024
  • Thumbnail for Homoscedasticity and heteroscedasticity
    to the value of x {\displaystyle x} . More generally, if the variance-covariance matrix of disturbance ε i {\displaystyle \varepsilon _{i}} across i {\displaystyle...
    27 KB (3,191 words) - 15:51, 29 May 2024
  • Thumbnail for Autocorrelation
    well defined. Subtracting the mean before multiplication yields the auto-covariance function between times t 1 {\displaystyle t_{1}} and t 2 {\displaystyle...
    39 KB (5,526 words) - 08:04, 28 April 2024
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