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Graph power. In graph theory, a branch of mathematics, the kth power Gk of an undirected graph G is another graph that has the same set of vertices, but in which two vertices are adjacent when their distance in G is at most k. Powers of graphs are referred to using terminology similar to that of exponentiation of numbers: G2 is called the ...
Power graph analysis is the computation, analysis and visual representation of a power graph from a graph (networks). Power graph analysis can be thought of as a lossless compression algorithm for graphs. [1] It extends graph syntax with representations of cliques, bicliques and stars. Compression levels of up to 95% have been obtained for ...
Dirichlet convolution is a special case of the convolution multiplication for the incidence algebra of a poset, in this case the poset of positive integers ordered by divisibility. The Dirichlet hyperbola method computes the summation of a convolution in terms of its functions and their summation functions.
Moment (mathematics) In mathematics, a quantitative measure of the shape of a set of points. In mathematics, the moments of a function are certain quantitative measures related to the shape of the function's graph. If the function represents mass density, then the zeroth moment is the total mass, the first moment (normalized by total mass) is ...
Together with rank statistics, order statistics are among the most fundamental tools in non-parametric statistics and inference. Important special cases of the order statistics are the minimum and maximum value of a sample, and (with some qualifications discussed below) the sample median and other sample quantiles.
The distribution is named after Lord Rayleigh (/ ˈreɪli /). [1] A Rayleigh distribution is often observed when the overall magnitude of a vector in the plane is related to its directional components. One example where the Rayleigh distribution naturally arises is when wind velocity is analyzed in two dimensions.
k. -nearest neighbors algorithm. In statistics, the k-nearest neighbors algorithm (k-NN) is a non-parametric supervised learning method first developed by Evelyn Fix and Joseph Hodges in 1951, [1] and later expanded by Thomas Cover. [2] It is used for classification and regression. In both cases, the input consists of the k closest training ...
The harmonic number with = ⌊ ⌋ (red line) with its asymptotic limit + (blue line) where is the Euler–Mascheroni constant.. In mathematics, the n-th harmonic number is the sum of the reciprocals of the first n natural numbers: [1] = + + + + = =.