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Distribution Theory is a specialized category for books that study the mathematics of “distributions” in two closely related senses. In statistics, it covers the structure and properties of probability distributions—univariate and multivariate families, transformations, sampling distributions, order statistics, limit theorems, and asymptotic approximations—that underpin estimation, hypothesis testing, and stochastic modeling. In analysis, it includes the theory of distributions (generalized functions) in the sense of Schwartz, such as test function spaces, tempered distributions, weak derivatives, convolution, and Fourier/Fourier–Laplace transforms, with applications to partial differential equations, signal processing, and mathematical physics. This category includes rigorous introductions, reference handbooks, and advanced monographs for graduate-level readers and researchers.

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