• 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 (4,739 words) - 16:25, 8 October 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...
    35 KB (5,447 words) - 03:53, 8 October 2024
  • average) or empirical mean (empirical average), and the sample covariance or empirical covariance are statistics computed from a sample of data on one or more...
    13 KB (2,206 words) - 10:24, 20 March 2024
  • Look up covariance or contravariance in Wiktionary, the free dictionary. Covariance and contravariance may refer to: Covariance and contravariance of...
    608 bytes (104 words) - 14:15, 16 September 2024
  • theory and statistics, the covariance function describes how much two random variables change together (their covariance) with varying spatial or temporal...
    4 KB (582 words) - 18:22, 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) - 00:21, 24 September 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) - 21:12, 2 August 2024
  • 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...
    58 KB (8,481 words) - 20:26, 21 September 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 (14,369 words) - 17:37, 9 October 2024