[R] what's interesting to plot after predict.lm?

From: agent dunham <crosspide_at_hotmail.com>
Date: Wed, 23 Mar 2011 09:04:39 -0700 (PDT)


Dear all,

I've fitted this model with train data

lms <- lm(vd ~ log(v1) + fv2+ fv5+ fv7 )

and predicted over test data using

plms <- predict.lm(lmsub, new=test,interval="predict", level=0.95,se.fit=TRUE)

I've two questions:

q1: what's the difference between writing interval "predict" or "confidence" ? How are they computed?

     Any reference would be appreciated

q2: What's interesting to plot? I've gone through another post, and have seen the following:    

(http://r.789695.n4.nabble.com/help-with-predict-and-plotting-confidence-intervals-td886399.html)

                    plot( seq(0,6, length.out = 24),  plmsub[ ,"fit"] ) 
                    lines(seq(0,6, length.out = 24),  plmsub[ ,"lwr"],
lty=2) 
                    lines(seq(0,6, length.out = 24),  plmsub[ ,"upr"],
lty=2) 
     But I don't know what to plot with my multiple linear regression.

     I also tried plot(plms) but I guess it doesn't have too much sense

     Maybe test$vd vs plms$fit? (if this was correct, what's the syntax to
get the fit column of plms? )     

Thanks in advance, user_at_host.com

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Received on Wed 23 Mar 2011 - 18:37:36 GMT

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