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2% after nal washing (Sofos et al 1999b, d) It was more dif cult to meet the performance criteria during the wet (November through January) than the.

happens in Figure 221 during each of the rst few months after smoking cessation When this happens, ex-smokers are at greater risk of relapse Examining the changing slope of the survivor function is one way to identify such risky time periods But a more sensitive way to assess the risk of event occurrence is to examine the hazard function, a mathematical function related to the survivor function that registers these changing slopes of the (negative log) survivor function Mathematical de nitions of hazard differ depending on whether time is measured discretely or continuously In discrete time, events happen during nite intervals, such as months, semesters, or years In continuous time, events happen at precise instants, and event occurrence is recorded using units such as days or weeks (or perhaps even minutes or hours).

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tracking code (MODPATH; Pollock 1994) and a three-dimensional method of characteristics program (MOC3D; Konikow et al 1996) Customary practices for the use of such codes are now well established (eg Anderson and Woessner 1992; Hulme et al 2002; Rushton 2003), if not devoid of their critics (Konikow and Bredehoeft 1992) The typical sequence of activities is summarized in Figure 105 In applying the routine of Figure 105 to groundwater ow modeling, many practitioners rst calibrate a so-called steady-state model, ie a version of the model which purports to represent some average set of head conditions re ecting the balance between long-term recharge and discharge Because real aquifers are never in such a state, this practice requires acceptance of an inherent element of ction However, because it allows testing of alternative transmissivity values before adding the complication of variations in storativity,ix steady-state calibration remains popular in practice.

If time is measured discretely, hazard is de ned as the conditional probability that an ex-smoker will relapse in a particular time interval, given that the person has not relapsed prior to the interval As the interval length decreases, the probability that an event will occur during any given interval decreases as well In the limit, when time is measured continuously, we must modify the de nition of hazard because the probability that an event occurs at any in nitely thin instant of time will approach zero (by de nition) So continuous time hazard is de ned as the instantaneous rate of relapse, given uninterrupted abstinence until that time While hazard is always nonnegative, when time is measured discretely, it can never exceed 1; when time is measured continuously, it can assume any value greater than, or equal to, 0.

Proof. It suf ces to show that if an edge uv belongs to LMST, then it belongs to RNG. By contradiction, suppose there exists an edge uv such that uv [ LMST

Like the survivor function, the hazard function can be plotted against time, yielding a pro le of the risk of relapsing each month, given uninterrupted abstinence until that month The magnitude of each month s hazard indicates the risk of relapsing in that month the higher the hazard, the greater the risk Each month s hazard is calculated using data on only those individuals still eligible to experience the event during the month (the risk set); individuals who have already relapsed are not included The lower panel of Figure 221 presents the sample hazard function corresponding to the sample survivor function in the top panel The risk of relapse is high in each of the rst few months of the study and then declines over time.

Ex-smokers are at greatest risk of relapse immediately after they quit; those who successfully abstain for several months are likely to abstain for at least a year The hazard function is an invaluable analytical tool because it effectively portrays variation in risk of event occurrence over time We identify the moments of this variation by locating the hazard function s distinctive peaks and troughs Peaks pinpoint periods of elevated risk; troughs pinpoint periods of low risk We illustrate this approach in Figure 222..

Guest histories are marketing analyses of guests geographic and demographic information that also provide information about guest activities while staying at the hotel. This

The drawNewInfo function uses the document s getElementById call to extract information for the widget and draw it. This function inserts href tags into the artist and album names to build hyperlinks to the iTunes Music Store.

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