4: Multi-factor Regression

Linear Regression Using R - An Introduction to Data Modeling · LibreTexts

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    A multi-factor regression model is a generalization of the simple one- factor regression model discussed in Chapter 3. It has n factors with the form:

    y = a0 + a1x1 + a2x2 + ...anxn,

    where the xi values are the inputs to the system, the ai coefficients are the model parameters computed from the measured data, and y is the output value predicted by the model. Everything we learned in Chapter 3 for one- factor models also applies to the multi-factor models. To develop this type of multi-factor regression model, we must also learn how to select specific predictors to include in the model

    This page titled 4: Multi-factor Regression was last modified on Mon, 17 Aug 2020 19:27:40 GMT and is shared under a CC BY-NC 4.0 license and was authored, remixed, and/or curated by David Lilja (University of Minnesota Libraries Publishing) via source content that was edited to the style and standards of the LibreTexts platform.