## Simulation modeling and analysisThis authoritative, comprehensive, and thoroughly up-to-date guide addresses all the important aspects of a simulation study, including modeling, simulation languages, validation, input probability distribution, and analysis of simulation output data. Full scale treatments of manufacturing systems simulation and simulation software and animation are also included along with useful and instructive case studies. |

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Page 255

f(.x)L Shaded area = 1 — a endpoints have been

correct interpretation to give to the confidence interval (4.11) is as follows [see (

4.10)]: If one constructs a very large number of independent 100(1 — a) percent ...

f(.x)L Shaded area = 1 — a endpoints have been

**given**numerical values. Thecorrect interpretation to give to the confidence interval (4.11) is as follows [see (

4.10)]: If one constructs a very large number of independent 100(1 — a) percent ...

Page 480

8.5.2 Multivariate Normal and Multivariate Lognormal The </-dimensional

multivariate normal distribution with mean vector \i = (fiy, fi2, . . . , fi.d)T and

covariance matrix 2, where the (/, j')th entry is atJ, has joint density function

in Sec.

8.5.2 Multivariate Normal and Multivariate Lognormal The </-dimensional

multivariate normal distribution with mean vector \i = (fiy, fi2, . . . , fi.d)T and

covariance matrix 2, where the (/, j')th entry is atJ, has joint density function

**given**in Sec.

Page 506

D where the sample variance S2(n) is

confidence interval based on (9.1) the fixed-sample-size procedure. EXAMPLE

9.14. For the bank of Example 9.1, suppose that we want to obtain a point

estimate and an ...

D where the sample variance S2(n) is

**given**by Eq. (4.4). We will call theconfidence interval based on (9.1) the fixed-sample-size procedure. EXAMPLE

9.14. For the bank of Example 9.1, suppose that we want to obtain a point

estimate and an ...

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### Contents

Basic Simulation Modeling | 1 |

FixedIncrement Time Advance | 93 |

Problems | 99 |

Copyright | |

21 other sections not shown

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### Common terms and phrases

acceptance-rejection method algorithm alias method approach average delay batch Chap confidence interval configurations correlation covariance-stationary define delay in queue density function discrete discussed in Sec distribution function estimate event list event type example exponential distribution exponential random factors FIFO FIGURE forklift FORTRAN fprintf(outfile gamma gamma distribution given histogram idle independent initial integer interarrival inverse-transform method job type machine manufacturing system mean metamodel Note number in queue number of customers observations obtain output data percent confidence interval plot Poisson process Prob probability procedure Q-Q plot queueing model queueing system random numbers random variables replications sample sampst scale parameter scheduled server sim_time simlib simulation simulation model simulation packages simulation run simulation study single-server queueing specified station statistical steady-state stochastic stochastic process Suppose Table teller throughput tion update valid variance variates vector Weibull Weibull distribution