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- W2336227550 abstract "In many situations, processes are often represented by a function that involves a response variable and a number of predictive variables. In this chapter, we show how to treat data whose relation between the predictive and response variables is nonlinear and, as a consequence, cannot be adequately represented by a linear model. This kind of data are known as nonlinear profiles. Our aim is to show how to build nonlinear control limits and a baseline prototype using a set of observed in-control profiles. Using R, we show how to afford situations in which nonlinear profiles arise and how to plot easy-to-use nonlinear control charts." @default.
- W2336227550 created "2016-06-24" @default.
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- W2336227550 date "2015-01-01" @default.
- W2336227550 modified "2023-10-18" @default.
- W2336227550 title "Nonlinear Profiles with R" @default.
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- W2336227550 doi "https://doi.org/10.1007/978-3-319-24046-6_10" @default.
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