multiple regression? [General Sta­tis­tics]

posted by Helmut Homepage – Vienna, Austria, 2017-10-08 17:17  – Posting: # 17875
Views: 14,503

Hi ElMaestro,

nice setup. Given

» […] a lot of knobs and buttons and sliders that allow me to tweak combinations of:
» - Tesla coil zap modifier strength
» - Evil discharge combobulator intensity
» - Ion stream barbaric voltage gain
» - Apocalyptic wolfram anode ray modulation
» ...and so forth.

I’m I right that you are aiming at multiple regression (i.e., >1 regressor and and one regressand)? See there for an arsenal of methods. For the same number of regressors the adjusted R2 takes the number of data points into account.

x1 <- rnorm(10)
y1 <- x1*2+rnorm(10, 0, 0.1)
muddle1 <- lm(y1 ~ x1)
R2.adj1 <- summary(muddle1)$adj.r.squared
x2 <- x1[-1] # drop 1
y2 <- y1[-1] # drop 1
muddle2 <- lm(y2 ~ x2)
R2.adj2 <- summary(muddle2)$adj.r.squared
cat(R2.adj1, R2.adj2, "\n")


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