Hello, Hoe did you get 0.002? Can you ?dput your data?
d <- read.table(text = " factor observation -0.003 -2 -0.002 -2 -0.001 -1 0.000 1 0.001 0 0.002 1 0.003 2 ", header = TRUE) fit <- lm(observation ~ 0 + factor, data = d) summary(fit) # R2 is 0.8595, not 0.002 Hope this helps, Rui Barradas Em 04-08-2013 18:19, CHEN, Cheng escreveu:
Hi gurus! What I need to do is to find a model, which can predict what the * observation* should look like given a *factor* input. i am doing a simple linear fit in R: lm(observation~0+factor, data=d), the R^2 is 0.002, which is really small. however, when I do a 'SELECT AVG observation by 0.001 BRACKET factor', there result is something like: *factor* | *average observersion* -0.003 -2 -0.002 -2 -0.001 -1 0.000 1 0.001 0 0.002 1 0.003 2 from a user perspective, i definitely see a pattern here, but somehow this pattern is not captured by a linear model. Is my understanding correct? so R gurus, which model do you suggest me to try for such data? Thanks!
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