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A more efficient algorithm can be obtained if we use a data structure that supports accessing the kth smallest item (in logarithmic time) Doing so allows us to implement each round of passing in a single operation Figure 141 shows why Suppose that we have N players remaining and are currently at player P from the front Initially N is the total number of players and P is 1 After M passes, a calculation tells us that we are at player ( ( P + M ) mod N) from the front, except if that would give us player 0 , in which case, we go to player N The calculation is fairly tricky, but the concept is not Applying this calculation to Figure 141, we observe that M is 1, N is initially 5, and P is initially 1 So the new value of P is 2 After the deletion, N drops to 4, but we are still at position 2, as part (b) of the figure suggests The next value of P is 3, also shown in part (b), so the third element in the list is deleted and N falls to 3 The next value of P is 4 mod 3, or 1, so we are back at the first player in the remaining list, as shown in part (c) This player is removed and N becomes 2 At this point, we add M to P, obtaining 2 Because 2 mod 2 is 0 , we set P to player N, and thus the last player in the list is the one that is removed This action agrees with part (d) After the removal, N is 1 and we are done

If we implement each round of passing in a single logarithmic operation, the simulation will be faster

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In terms of the observed data, the model is ( 1.2) for i = 1,2, ... , n. Also included in the model is the assumption that the random errors e l , e 2 , , en can be regarded as a random sample of independent draws from a single population having a mean of O. When Is the Model Appropriate If we have a set of data which we want to analyze by linear regression, how can we tell if the linear regression model is appropriate for these data In the first place, it must be realized that a

last->next = new Node; last = last->next; last->item = x; last->next = NULL;

// // // //

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An arbitrary item can no longer be found in one access Instead, we must scan down the list This difference is similar to that of accessing an item on a compact disk (one access) or a tape (sequential) On the other hand, inserting a new element between two existing elements requires much less data movement in a linked list than in an array We present a more detailed description of the linked list in s 16 and 17

= 64G 2(k p')(k', p),

Summary

theoretical model can never exactly describe a real-world process such as the production of vitamin B2 in turnip leaves, because the real world is too complex. But for the model to be useful, the data should appear to approximately follow the model. The linear regression model makes several assumptions about the data, including linearity of the function of the explanatory variables, independence of the random errors, and equality of the variances of the random errors. Procedures have been developed for checking the approximate validity of these assumptions. Some of these procedures are discussed in 2.

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(12.35)

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