Monte Carlosimulation
- Random number generation (RNG)
  • 05`5.Uniform (mid-square, congruential, etc.) • 08`7.~Binomial, Poisson (rev. 18`b) • 03`7.Gaussian, Exponential, Beta (with 'sendmail')
• 12`4.^~Integer randbetween (rev. 18`b)
• Transforms [inversion, acceptance-rejection]
Inversion • 04`a.One value (Gaussian, triangular) • Some notes (parabolic, truncated Gaussian, etc.)
• 07`5.^~Parabolic distribution (rev. 18`b) • 12`b.^~"Raised" cosine distr. • $* 16`4.^~Weibull distr. (under constr.) • 17`4.^~oblique distr.
Acceptance-rejection • 08`2.^~Triangular distr. • 08`2.^~parabolic distr. • 08`2.^~cosine distr. (for "hat" optimization)
— Tansform 08`1.^~Gaussian RN ###comparison (inv., AR, Box-Muller, modBM) • 10`a.^~GRNG (Gaussian [Thomas et al., 2007])
- Monte Carlo integration
  • 17`a.^~Simple vs. importance sampling • 17`c.^~integration 2D
- Monte Carlo simulation   (OR, Oper. Res.; QC, Q. Control; Mi, misc.)
  • QC 05`b.^~"Fishes on Venus" • QC or OR 15`a.^~Simulate various variables (Exponential, Gaussian, triangular) • OR 99`3.^Product of 2 numbers • 02`a.^Monty Hall paradox • 19`b.^~Dice throwing • OR 07`5.^~Light bulbs lifetime (better: see Quality) • 11`c.^~Chord length • Mi 15`5.^~Euromillions
• Determinants (random): 12`2.^~continuous, 13`6.^~integer
• Distances (random): 13`2.^~Interdistance in an n-cube. 14`1.^~In a circle. 14`1.^~In a rectangle.
• Triangles (random): 16`c.^~Area given perimeter • 09`b.^~Concentrations
• Uniforms: 09`6.^~sum*; 03`b.^~product of 2 (analytical)
• Gaussians: 04`a.^~sums, products; 09`9.^~sum of 2 with (3) graphs (←) 20`6.^~Bruno Franco §sum of two (ditto)
• Simulate 20`b.^~spheres (Fortran) • 20`c.^~spheres (Python)
• Correlation: 17`7.^~Tiles with (2D) correlated sides; 17`8.Cholesky decompositions; 17`8.^~Bricks with (3D) correlated sides
• Truncated Gaussian: 11`5.^~simulated 17`4.^~sum of truncated Gaussians 11`9.~analytical (• Simulated for ###12`3.~regression)
• Filling • 04`4.^~Bag f.1:2004 (§ 09`9.^~or 2:2009) • 13`b.^~Bag f. 3:2013
• CISTI'2018Bags for σ: see 'bags' at Quality tools
• Biscuit • 13`7.^~Packets; 09`9.^~Slices; with 17`5.^~specs
• 13`8.^~Estimation from unequal size samples
• ^~Packet 10`9.tube-style f., 10`9.second, 11`9.third (Nazaré), (10`4.old); 13`6.MPI (CISTI, Miguel Ferreira)
• Truck with (discrete) 05`5.^~binomial sacks (07`a.~&), with 09`5.^~truncated Gaussian sacks

• 13`4.^~Hopper (conical) • 14`6.^~Cone bottom cylinder • 16`4.^~Liquid in sphere • 13`4.^~Tank wagons • 15`a.^~Can filling • 14`8.^~Tying two rods • 19`5.^~Variation in consecutive values
• CISTI'2016, remote parallel: ^~15`9.Bag fill.. Inscribed triangles: ^~16`1.area; ^~16`1.perimeter. ^~16`2.provisional. Inscribed polygons: ^~16`1.perimeter.

- Bibliography
An unexpected, inadvertent change in the IST Library software broke former links.

• Ross, Sheldon M., 1988 (1976), "A first course in probability", Macmillan, New York, NY (USA) (ISBN: 013895772X), Ch. 15, "Sums of a random number of random variables", p 83. G'b 2002 (6.th ed.).

• NIST/SEMATECH e-Handbook of Statistical Methods, 1.3.3.14.Histogram (Engineering statistics handbook).

• Thomas, David B., Wayne Luk, Philip H. W. Leong, John D. Villasenor, 2007, "Gaussian random number generators".pdf, ACM Computing Surveys, vol. 39, issue 4, article 11, Oct..

• Virtual laboratories in Prob & Stat, Univ. Alabama in Huntsville.

• Blumenfeld, Dennis, 2001, "Operations Research calculations handbook", CRC Press, Boca Raton, FL (USA) (ISBN: 0-8493-2127-1).  G'b, p 10.

• Ross, Sheldon M., 2006, "Simulation", 4.th ed., Elsevier.

• Scott, David W., 1992, "Multivariate density estimation: theory, practice, and visualization", Wiley. (ISBN: 0-471-54770-0) (Histogram classes.)

• Romano, Joseph P., Andrew F. Siegel, 1986 (1986), "Counterexamples in probability and statistics", Wadsworth, Belmont, CA (USA) (ISBN: 0-534-05568-0). G'b 1986.

 
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