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In our previous discussion of the Z-count, we saw that the receiver can establish the time of transmission of the beginning of each subframe of the signal and of the corresponding C=A-code epoch that coincides with it. Since the epochs are transmitted precisely 1 ms apart, the receiver labels subsequent C=A-code epochs merely by counting them. This enables the determination of the transmission time of any part of the signal by a process to be described later. 3.5.2 Ephemeris Data

n = 1.515

(2.11)

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Parametric assumptions about the owgraph allow us to specify the likelihood function for complete data De nition 513 Complete data on the owgraph model consists of having every intermediate transition for each observation The associated waiting time for the transitions may be censored; however, the transition information is complete For example, in the owgraph for cancer progression of Figure 21, complete data on a patient consist of a history of all transitions made by that patient, say, I A R A D1 If the patient is censored in state A but we know that the patient eventually died from cancer, the waiting time for the transition A D1 is censored but the transition information is still considered to be complete In the context of owgraphs, incomplete data refers to data with incomplete transition information in addition to censoring We defer the discussion of incomplete data to 8.

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with owgraphs, we use the more stable CDF computed by numerically integrating the saddlepoint density approximation. The exact and saddlepoint approximated convolution densities of Figure 3.17 are virtually indistinguishable. A convolution of more than two Weibull distributions can be handled by the saddlepoint approximations through the addition of more terms to the CGF of T , while approximation by numerical integration necessitates evaluation of higher-dimensional integrals. In parametric modeling, there are a variety of distributions from which one can choose. This example illustrates that while the Weibull can be used in owgraph modeling, from the point of view of owgraph algebra, it is more convenient to use other distributions that can mimic the shape of the Weibull, such as the gamma or inverse Gaussian.

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