Brief notes on simulation of several variables

• Cosinusoidal and kindred densities (pdf) .pdf

• Simulation of a uniform variable

• Simulation of an exponential variable

• Simulation of an "oblique" variable

• Simulation of a "parabolic" variable — This distribution has   σ = a ⁄ √ 5 (.pdf).

• Simulation of a truncated Gaussian variable.pdf

• Simulation of a "cosinusoidal".xls variable

• Simulation of any variable:
  May lead (it usually does) to numerical methods, such as Newton-Raphson, to solve the (implicit) equation, Y = F(x), where Y is a (typically, uniform) random number and x is the random value sought.


References:
• Jensen, Eva B. Vedel — Simulation: stochastic sim..pdf (stochastic sim..pdf, see p 7, 2.4. Inversion) (simulering, Aarhus Univ.)
• Stockbridge, Richard H. — Simulation of random variables:
  inverse transformation method.pdf, rejection technique.pdf (Lect. notes 17 & 18.pdf) (MathStat, Univ. of Wisconsin-Milwaukee)
• Devroye, Luc —
• Generating Samples from Probability Distributions ← Urban Operations Research ← MIT
• Murthy, K. P. N. — "Monte Carlo: Basics" (Murthy0104215.pdf, see p 42, 10. Random sampling techniques) (IGCAR)
• Vujić, Jasmina — Vujic.pdf     (writing HTML, Using Unicode, Google search)
 
 
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Created: 2010-11-13 (2005.12.04) — Last modified: 2018-11-18