a. List two other names for the \"common random numbers\" variance reduction tec

Question

a. List two other names for the "common random numbers" variance reduction technique b. Pseudo random number sequences in Crystal Ball are controlled by specifying c. Pseudo random number sequences in Arena are controlled by specifying d. The K-S goodness of fit test is not applicable to e. In a discrete event simulation, the system state only changes at specific time points when values? g. Describe what cycling is with respect to the generation of pseudorandom numbers h. Name four continuous distributions for which an inverse transform method can be applied for random variate generation i. Name two distributions for which an inverse transform method cannot be applied for random variate generation. j. Name two different sampling approaches utilized in Monte Carlo simulation.

Explanation / Answer

Common Random Number:-

A-rationale

B- applicability

2) key generation

nonces

3)advanced transfer

advanced process

4)Binned data

5)in a discrete event simulation the system state only charges at specific time points when specified lenght occur

6) what is type nof LCG implemented in crystall ball and what are the parameter value :- it is defined as recursive formula =Zi=(aZi-1)(mod m)

7)cycling with respect to pseudorandom number and what are the parameter

numbers which will pass most of the statistical tests for randomness. However, if the program is rerun on a subsequent day the exact same stream of numbers will be produced. To overcome this problem, since the chain of numbers is very large, a starting seed which uses the current date and I.D. number of the user can be used to enter the chain at different points every time the program is run. a pseudo-random number generator is said to be full cycle if it leaves no gaps in the range of numbers it generates.

Form: X0 a given “seed”
Xi+1 = ( a Xi + c ) mod m

name four continous distribution for which an inverse transform method can be applied for random variate generation

The cumulative distribution function (cdf) technique

2. The probability density function (pdf) technique, univariate

3. The probability density function (pdf) technique, bivariate

4.  Discrete Random Variables

name two diistribution for which an inverse transform method cannot be applied for random vareint generation

Uniform Random Number Generation

Ad Hoc Methods

name two diffrent sampling approaches utilized in monte carlo simulation

pesudo random number sampling

low dispcrepancy sequence

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