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- Andrew G. Glen, Lawrence Leemis, John H. Drew
- Computational Statistics & Data Analysis
- 2004

We present an algorithm for computing the probability density function of the product of two independent random variables, along with an an implementation of the algorithm in a computer algebra system. We combine this algorithm with earlier work on transformations of random variables to create an automated algorithm for convolutions of random variables.… (More)

- Andrew G. Glen, Lawrence Leemis, Donald R. Barr
- IEEE Trans. Reliability
- 2001

We present an algorithm for computing the cumulative distribution function of the Kolmogorov{ Smirnov test statistic D n in the all-parameters-known case. Birnbaum (1952) gives an n-fold integral for the CDF of the test statistic which yields a function deened in a piecewise fashion, where each piece is a polynomial of degree n. Unfortunately, it is diicult… (More)

- Andrew G. Glen, Lawrence Leemis, John H. Drew
- INFORMS Journal on Computing
- 1997

We present a generalized version of the univariate change-of-variable technique for transforming continuous random variables. Extending a theorem from Casella and Berger 3] for many{to{1 transformations, we consider more general univari-ate transformations. Speciically, the transformation can range from 1{to{1 to many{to{1 on various subsets of the support… (More)

- Andrew G. Glen, B. L. Foote
- IEEE Trans. Reliability
- 2009

- Andrew G. Glen
- Computational Statistics & Data Analysis
- 2010

- Andrew G. Glen, Lawrence Leemis, Daniel J. Luckett
- 2016 Winter Simulation Conference (WSC)
- 2016

A method to produce new families of probability distributions is presented based on the incomplete gamma function ratio. The distributions distributions produced also can include a number of popular univariate survival distributions, including the gamma, chi-square, exponential, and half-normal. Examples that demonstrate the generation of new distributions… (More)

- Christopher E. Marks, Andrew G. Glen, +5 authors Lawrence M. LEEMIS
- 2014

Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views… (More)

- Andrew G. Glen
- Computers & Industrial Engineering
- 2010

0360-8352/$ see front matter Published by Elsevier doi:10.1016/j.cie.2010.01.008 q This manuscript was processed by Area Editor E.A * Tel.: +1 845 938 5988. E-mail address: andrew.glen@usma.edu A variation of maximum likelihood estimation (MLE) of parameters that uses probability density functions of order statistic is presented. Results of this method are… (More)

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