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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 ...
A matrix satisfying only the first of the conditions given above, namely + =, is known as a generalized inverse. If the matrix also satisfies the second condition, namely + + = +, it is called a generalized reflexive inverse. Generalized inverses always exist but are not in general unique.
At =, however, there is a problem: the graph of the square root function becomes vertical, corresponding to a horizontal tangent for the square function. = (for real x) has inverse = (for positive )
The graphs of y = f(x) and y = f −1 (x). The dotted line is y = x. If f is invertible, then the graph of the function = is the same as the graph of the equation = (). This is identical to the equation y = f(x) that defines the graph of f, except that the roles of x and y have
The product logarithm Lambert W function plotted in the complex plane from −2 − 2i to 2 + 2i The graph of y = W(x) for real x < 6 and y > −4.The upper branch (blue) with y ≥ −1 is the graph of the function W 0 (principal branch), the lower branch (magenta) with y ≤ −1 is the graph of the function W −1.
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 ...
The inverse x(F) may not exist because the cumulative distribution function has intervals of constant values. However, the previous formula can still apply by generalizing the definition of x(F): = {: ()} where inf is the infimum. For an example of a Lorenz curve, see Pareto distribution.
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.