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In mathematics, and in particular, algebra, a generalized inverse (or, g-inverse) of an element x is an element y that has some properties of an inverse element but not necessarily all of them. The purpose of constructing a generalized inverse of a matrix is to obtain a matrix that can serve as an inverse in some sense for a wider class of ...
For the cases where has full row or column rank, and the inverse of the correlation matrix ( for with full row rank or for full column rank) is already known, the pseudoinverse for matrices related to can be computed by applying the Sherman–Morrison–Woodbury formula to update the inverse of the ...
The Fréchet distribution, also known as inverse Weibull distribution, [2] [3] is a special case of the generalized extreme value distribution. It has the cumulative distribution function ( ) = > . where α > 0 is a shape parameter.
Let A be a square n × n matrix with n linearly independent eigenvectors q i (where i = 1, ..., n).Then A can be factored as = where Q is the square n × n matrix whose i th column is the eigenvector q i of A, and Λ is the diagonal matrix whose diagonal elements are the corresponding eigenvalues, Λ ii = λ i.
Download as PDF; Printable version; In other projects ... Inverse; General Leibniz; Faà di Bruno's formula; ... Template: Calculus is used to ...
The inverse Gaussian distribution is a two-parameter exponential family with natural parameters −λ/(2μ 2) and −λ/2, and natural statistics X and 1/X. For λ > 0 {\displaystyle \lambda >0} fixed, it is also a single-parameter natural exponential family distribution [ 4 ] where the base distribution has density
Graph of the density of the inverse of the standard normal distribution. If variable X follows a standard normal distribution (,), then Y = 1/X follows a reciprocal standard normal distribution, heavy-tailed and bimodal, [2] with modes at and density
The inverse function theorem can also be generalized to differentiable maps between Banach spaces X and Y. [20] Let U be an open neighbourhood of the origin in X and F : U → Y {\displaystyle F:U\to Y\!} a continuously differentiable function, and assume that the Fréchet derivative d F 0 : X → Y {\displaystyle dF_{0}:X\to Y\!} of F at 0 is ...