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THE H-FUNCTION AND PROBABILITY DENSITY FUNCTIONS OF CERTAIN ALGEBRAIC COMBINATIONS OF INDEPENDENT RANDOM VARIABLES WITH H-FUNCTION PROBABILITY DISTRIBUTIONS

Posted on:1982-03-02Degree:Ph.DType:Dissertation
University:The University of Texas at AustinCandidate:COOK, IVY DEWEY, JRFull Text:PDF
GTID:1470390017465381Subject:Statistics
Abstract/Summary:
A practical technique is presented for determining the exact probability density function and cumulative distribution function of a sum of any number of terms involving any combination of products, quotients, and powers of independent random variables with H-function distributions. The H-function is the most general named function, encompassing as special cases most of the other special functions of mathematics and many of the classical statistical distributions. Its unique properties make it a powerful tool for statistical analysis. In particular, the product, quotient, and powers of independent H-function variates are also H-function variates, and the Laplace and Fourier transforms and the derivatives of an H-function are readily-determined H-functions.; This dissertation first provides background material, including history on H-functions and the algebra of random variables, definitions and properties of integral transforms, theorems on transformations of random variables, and definition, properties and special cases of the H-function. For determining whether convergence of a general Mellin-Barnes integral or an H-function occurs with left-half-plane versus right-half-plane summation of residues, evaluation guidelines are formally established and applied to the known special cases, the Laplace transform, and the derivatives of the H-function. Then, a new, improved formulation for evaluation of an H-function by summing residues is derived. This formulation is combined with a Laplace transform numerical inversion method to give a second new formulation.; The definition, special cases, and transformation theorems for the H-function distribution are presented. A new formula for finding the constant of an H-function distribution is derived. Also, the cumulative distribution function of an H-function distribution is shown to be a convergent H-function, and a more efficient way to compute it is found. Demonstration of the practical technique for handling sums is accompanied by an implementing computer program. Some examples of areas of application are discussed.; Throughout this dissertation, a number of new H-function formulas are found, including relations between given H-functions and other named functions or lower order H-functions, special-case derivative rules, and improved transform and derivative formulas.
Keywords/Search Tags:H-function, Distribution, Random variables, Probability, Special, Independent
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