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Quality and Reliability Methods - SAS

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Chapter 15 Recurrence Analysis 275<br />

Fit Model<br />

Homogeneous Poisson Process<br />

I(t) = e γ te γ<br />

C(t) =<br />

where t is the age of the product.<br />

Table 15.1 defines each model parameter as a scale parameter or a shape parameter.<br />

Table 15.1 Scale <strong>and</strong> Shape Parameters<br />

Model Scale Parameter Shape Parameter<br />

Power NHPP θ β<br />

Proportional Intensity PP γ δ<br />

Loglinear NHPP γ δ<br />

Homogeneous PP γ none<br />

Note the following:<br />

• For the Recurrence Model Specification window (Figure 15.12), if you include Scale Effects or Shape<br />

Effects, the scale <strong>and</strong> shape parameters in Table 15.1 are modeled as functions of the effects. To fit the<br />

models with constant scale <strong>and</strong> shape parameters, do not include any Scale Effects or Shape Effects.<br />

• The Homogeneous Poisson Process is a special case compared to the other models. The Power NHPP<br />

<strong>and</strong> the Proportional Intensity Poisson Process are equivalent for one-term models, but the Proportional<br />

Intensity model seems to fit more reliably for complex models.<br />

Click Run Model to fit the model <strong>and</strong> see the model report (Figure 15.13).<br />

Figure 15.13 Model Report<br />

The report has the following options on the red triangle menu:<br />

Profiler<br />

launches the Profiler showing the Intensity <strong>and</strong> Cumulative functions.<br />

Effect Marginals evaluates the parameter functions for each level of the categorical effect, holding other<br />

effects at neutral values. This helps you see how different the parameter functions are between groups.<br />

This is available only when you specify categorical effects.

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