enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. File:High School Probability and Statistics (Basic).pdf

    en.wikipedia.org/wiki/File:High_School...

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  3. Matrix (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Matrix_(mathematics)

    For example, if A is a 3-by-0 matrix and B is a 0-by-3 matrix, then AB is the 3-by-3 zero matrix corresponding to the null map from a 3-dimensional space V to itself, while BA is a 0-by-0 matrix. There is no common notation for empty matrices, but most computer algebra systems allow creating and computing with them.

  4. Stochastic matrix - Wikipedia

    en.wikipedia.org/wiki/Stochastic_matrix

    A substochastic matrix is a real square matrix whose row sums are all ; In the same vein, one may define a probability vector as a vector whose elements are nonnegative real numbers which sum to 1. Thus, each row of a right stochastic matrix (or column of a left stochastic matrix) is a probability vector.

  5. Scatter matrix - Wikipedia

    en.wikipedia.org/wiki/Scatter_matrix

    Download as PDF; Printable version; ... see scattering matrix. In multivariate statistics and probability theory, the scatter matrix is a statistic that is used to ...

  6. Wishart distribution - Wikipedia

    en.wikipedia.org/wiki/Wishart_distribution

    Suppose G is a p × n matrix, each column of which is independently drawn from a p-variate normal distribution with zero mean: = (, …,) (,). Then the Wishart distribution is the probability distribution of the p × p random matrix [4]

  7. Dirichlet distribution - Wikipedia

    en.wikipedia.org/wiki/Dirichlet_distribution

    Download as PDF; Printable version; ... In probability and statistics, the Dirichlet distribution ... The matrix is thus singular.

  8. Matrix normal distribution - Wikipedia

    en.wikipedia.org/wiki/Matrix_normal_distribution

    The probability density function for the random matrix X (n × p) that follows the matrix normal distribution , (,,) has the form: (,,) = ⁡ ([() ()]) / | | / | | /where denotes trace and M is n × p, U is n × n and V is p × p, and the density is understood as the probability density function with respect to the standard Lebesgue measure in , i.e.: the measure corresponding to integration ...

  9. Multivariate normal distribution - Wikipedia

    en.wikipedia.org/wiki/Multivariate_normal...

    The probability content of the multivariate normal in a quadratic domain defined by () = ′ + ′ + > (where is a matrix, is a vector, and is a scalar), which is relevant for Bayesian classification/decision theory using Gaussian discriminant analysis, is given by the generalized chi-squared distribution. [17]