By M. A. Crane, A. J. Lemoine (eds.)

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**Additional info for An Introduction to the Regenerative Method for Simulation Analysis**

**Sample text**

Define state is entered, where we set Rk as the RI m 0 kth time that this "like-new" That is, the by the times that the repair facility becomes empty. Rk'S are defined Note, at each of these times there are i0 operating units and 5 fully repaired units in the spare pool. Furthermore~ because of the "lack of memory" property of the failure times, the operating units behave identically as they behaved when they were new. Thus~ at each time time RI = 0 prior to ~ the system appears identical as it did at , and its future behavior is also independent of its behavior Rk In other words, or regenerates "real-world" ~ the system "starts afresh" probabilistically, itself, at each time ~ The same is of course true of its counterpart.

And ~. for each cycle j ~ where Y. is 3 3 3 the sum of f ( X i ) over the jth cycle and ~j is the length of the 3. n jth cycle. Compute the sample statistics I n 7 I% , ~ = - j=l n , r = j~1 IIn performing these calculations; particularly those of Sll 3 s12 ~ and soo; it is wise to use double-precision arithmetic in order to [~sur~ the desY~ed degree of accuracy in computing the sums. 44 n n 2 i Sll - se2 n-I j=l S12 i n j=l - 2 s . 5. J = n ii n n j=l j=l n-I ^ = n Sll - 2 r s 1 2 " ^2 + r s22 Form the confidence interval ^ r± where z 5 = ~-i(i - 5) z~ s TNand is the standard normal distribution function.

Are given for the parameters PCx= 0} , E[71) , Theoretical values and 95~ confidence intervals E[X] and E~Tl) 2 . 325] P[X > 5} o. 5 Tactical questions We now discuss the questions of simulation run length in the context of regenerative simulations. We also show how the regenerative approach can be used in cases where a flxed-length simulation is desired (rather than a fixed number of cycles). Finally~ we discuss selection of the regenerative points in the case where a simulationmay have two or more possible choices for such regeneration points.