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In this part we describe some engineering applications. We start with a heteroscedastic parabolic regression model, in which the parameters are considered as random instead of deterministic. Since in the deterministic version we can plot percentile regression curves, with this model each percentile curve has its own percentiles curves. The second example is a powerful non-linear random fatigue example, which is selected to satisfy some engineering, physical and statistical conditions and is enriched by assuming that its five parameters are random variables. In this way, each of the S-N percentile curves of the model can be given as stochastic processes, whose percentiles are obtained. Several deal data sets are used to fit the models.
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