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Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

3 votes
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Noise has 0 mean

In regression settings, we want to approximate the response $y$ by a function $f$ of the input vector $x$ as good as possible by estimating $f$ from the data. … In linear regression, however, the restriction is much stronger. There one assumes (amongst other) that $E(\varepsilon \mid x) = 0$ (strict exogeneity). …
Michael M's user avatar
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2 votes
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How the term "R-squared" in VIF(variance inflation factor) is different from normal R-square...

It is calculated in the same way. Instead of the response variable $y$ of the original model with numeric regressors $x_1, \dots, x_p$, the response of the VIF-model is $x_i$ and the regressors all ot …
Michael M's user avatar
  • 499