Abstract
This chapter shows how to transform the continuous uniform random variates, u∼U(0,1), to random variates for a variable that comes from one of the common continuous probability distributions. The probability distributions described here are the following: the continuous uniform, exponential, Erlang, gamma, beta, Weibull, normal, lognormal, chi-square, student’s t, and Fishers F. The chapter also shows how to use the (Hasting’s) approximation formulas for the standard normal distribution.
Keywords
- Cumulative Distribution Function
- Standard Normal Distribution
- Approximation Formula
- Gamma Variate
- Continuous Uniform
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References
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Hastings Jr., C.: Approximation for Digital Computers. Princeton University Press, Princeton (1955)
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Thomopoulos, N.T. (2013). Generating Continuous Random Variates. In: Essentials of Monte Carlo Simulation. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6022-0_4
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DOI: https://doi.org/10.1007/978-1-4614-6022-0_4
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