Say I have a dataset full of observations and I run a regression model. Is there a package that can help me identify the observation that best "fits" the model?
Hi, and welcome!
A reproducible example, called a reprex always helps clarify questions. I'll have to assume that you mean an ordinary least squares regression using
reprex would look like
fit <- lm(mpg ~ wt, data = mtcars) abs_fit <- abs(fit$residuals) sort(abs_fit) #> Merc 450SL #> 0.0502472
Created on 2020-01-15 by the reprex package (v0.3.0)
This interprets the best fit as meaning has the smallest absolute residual, meaning lies closest to the trend line..
Do you mean the observation with the smallest residual?
Yes. @technocrat's response was perfect. Thank you!
Great. Please mark the solution for the benefit of those to follow. Do this even for your own solution, no false modesty. And, so far as I know,
a penny a point, ain't no one keeping score
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