APPL: A probability programming language. Statistical packages have been used for decades to analyze large datasets or to perform mathematically intractable statistical methods. These packages are not capable of working with random variables having arbitrary distributions. This article presents a prototype probability package named APPL (A Probability Programming Language) that can be used to manipulate random variables. Examples illustrate its use.

References in zbMATH (referenced in 11 articles )

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  1. Drew, John H.; Evans, Diane L.; Glen, Andrew G.; Leemis, Lawrence M.: Computational probability. Algorithms and applications in the mathematical sciences (2017)
  2. Jaroszewicz, Szymon; Korzeń, Marcin: Arithmetic operations on independent random variables: a numerical approach (2012)
  3. Kaczynski, William H.; Leemis, Lawrence M.; Drew, John H.: Transient queueing analysis (2012)
  4. Yang, Jeff X.; Drew, John H.; Leemis, Lawrence M.: Automating bivariate transformations (2012)
  5. Glen, Andrew G.: Accurate estimation with one order statistic (2010)
  6. Posch, Peter N.: A survey on sequences and distribution functions satisfying the first-digit-law (2008)
  7. Mercier, Sophie: Discrete random bounds for general random variables and applications to reliability (2007)
  8. Evans, Diane L.; Leemis, Lawrence M.; Drew, John H.: The distribution of order statistics for discrete random variables with applications to bootstrapping (2006)
  9. Leemis, Lawrence M.; Duggan, Matthew J.; Drew, John H.; Mallozzi, Jeffrey A.; Connell, Kerry W.: Algorithms to calculate the distribution of the longest path length of a stochastic activity network with continuous activity durations (2006)
  10. Evans, D.L.; Leemis, L.M.: Algorithms for computing the distributions of sums of discrete random variables (2004)
  11. Glen, Andrew G.; Leemis, Lawrence M.; Drew, John H.: Computing the distribution of the product of two continuous random variables (2003)