Elements of SimulationThis book provides a guide to the elements of simulation in statistics, which will include developments and which may be used either as a teaching text or as a source of reference. It is widely used for teaching statistics in schools. |
Contents
1 | 1 |
2 | 8 |
3 | 46 |
4 | 68 |
98 | 117 |
Variance reduction and integral estimation | 160 |
Model construction and analysis | 190 |
Further examples and applications | 209 |
Testing routines available in NAG and IMSL | 246 |
Solutions and comments for selected exercises | 264 |
| 307 | |
| 326 | |
| 336 | |
| 337 | |
| 343 | |
Computer algorithms for generation testing and design | 236 |
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Common terms and phrases
algorithm analysis antithetic variates applied approximation BASIC program binomial Biometrika bivariate Box-Muller Box-Muller method Cauchy distribution chapter chi-square test consider continuous random variables control variate correlation cumulative distribution function cycle length decimal density function f(x described discrete random variables Equation estimate example exponential distribution exponential random variables further discussion fx(x gamma given histogram illustration IMSL routine independent random variables independent U(0 integral interval inversion method investigate M/M/1 queue Markov mean MINITAB mixed congruential Monte Carlo multiplicative congruential N₁ N₂ needle normal distribution normal random variables obtained P₁ parameter points Poisson distribution Poisson process population Pr(X probability density function pseudo-random numbers random numbers random sample range rejection method result Section A1.1 sequence simple simulate random variables Table table-look-up method U₁ U₂ values variance reduction waiting-time X₁
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