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  2. Matrix similarity - Wikipedia

    en.wikipedia.org/wiki/Matrix_similarity

    This means that one may use Jordan forms that only exist over a larger field to determine whether the given matrices are similar. In the definition of similarity, if the matrix P can be chosen to be a permutation matrix then A and B are permutation-similar; if P can be chosen to be a unitary matrix then A and B are unitarily equivalent.

  3. Matrix equivalence - Wikipedia

    en.wikipedia.org/wiki/Matrix_equivalence

    In linear algebra, two rectangular m-by-n matrices A and B are called equivalent if = for some invertible n-by-n matrix P and some invertible m-by-m matrix Q.Equivalent matrices represent the same linear transformation V → W under two different choices of a pair of bases of V and W, with P and Q being the change of basis matrices in V and W respectively.

  4. Ratio of uniforms - Wikipedia

    en.wikipedia.org/wiki/Ratio_of_uniforms

    Rejection sampling of a bounded statistical distribution with finite support. A convenient technique to sample a statistical distribution is rejection sampling.When the probability density function of the distribution is bounded and has finite support, one can define a bounding box around it (a uniform proposal distribution), draw uniform samples in the box and return only the x coordinates of ...

  5. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    Clustering or Cluster analysis is a data mining technique that is used to discover patterns in data by grouping similar objects together. It involves partitioning a set of data points into groups or clusters based on their similarities. One of the fundamental aspects of clustering is how to measure similarity between data points.

  6. Similarity invariance - Wikipedia

    en.wikipedia.org/wiki/Similarity_invariance

    In linear algebra, similarity invariance is a property exhibited by a function whose value is unchanged under similarities of its domain. That is, f {\displaystyle f} is invariant under similarities if f ( A ) = f ( B − 1 A B ) {\displaystyle f(A)=f(B^{-1}AB)} where B − 1 A B {\displaystyle B^{-1}AB} is a matrix similar to A .

  7. Homogeneity and heterogeneity (statistics) - Wikipedia

    en.wikipedia.org/wiki/Homogeneity_and...

    They relate to the validity of the often convenient assumption that the statistical properties of any one part of an overall dataset are the same as any other part. In meta-analysis, which combines the data from several studies, homogeneity measures the differences or similarities between the several studies (see also Study heterogeneity).

  8. Relationships among probability distributions - Wikipedia

    en.wikipedia.org/wiki/Relationships_among...

    X (X) is a standard uniform (0,1) random variable; If X is a normal (μ, σ 2) random variable then e X is a lognormal (μ, σ 2) random variable. Conversely, if X is a lognormal (μ, σ 2) random variable then log X is a normal (μ, σ 2) random variable. If X is an exponential random variable with mean β, then X 1/γ is a Weibull (γ, β ...

  9. Isotropy - Wikipedia

    en.wikipedia.org/wiki/Isotropy

    A similar concept is homogeneity. Isotropic quadratic form A quadratic form q is said to be isotropic if there is a non-zero vector v such that q(v) = 0; such a v is an isotropic vector or null vector. In complex geometry, a line through the origin in the direction of an isotropic vector is an isotropic line. Isotropic coordinates