dimitris kapetanakis
2009-Feb-16 21:54 UTC
[R] incl.non.slopes=FALSE does not work at predict.lm
Dear all, I am trying to estimate the prediction from a fixed effects model and their confidence intervals as well. Though I do not want to include in the prediction and at the confidence intervals the intercept. For that reason I used the argument incl.non.slopes=FALSE. But either if it is TRUE or FALSE it does not have any difference and also the system does not provide any warning. I really cannot understand what is happening and I use both predict and predict.lm but there is no difference. Explicitly the code is: fe.nox <- lm(nox~ state.1 + state.2 + state.3 + state.4 + state.5 + state.6 + state.7 + state.8 + state.9 + time.1 + time.2 + time.3 + time.4 + time.5 + time.6 + time.7 + pcinc + I(pcinc^2) + I(pcinc^3), data=ekc) p.fe.nox<-predict.lm(fe.nox, new, interval = "prediction", level=0.95, incl.non.slopes=FALSE) Any Help would be highly appreciated Thanks Dimitris -- View this message in context: http://www.nabble.com/incl.non.slopes%3DFALSE-does-not-work-at-predict.lm-tp22046749p22046749.html Sent from the R help mailing list archive at Nabble.com.
On 17/02/2009, at 10:54 AM, dimitris kapetanakis wrote:> > Dear all, > > I am trying to estimate the prediction from a fixed effects model > and their > confidence intervals as well. Though I do not want to include in the > prediction and at the confidence intervals the intercept. For that > reason I > used the argument incl.non.slopes=FALSE. But either if it is TRUE > or FALSE > it does not have any difference and also the system does not > provide any > warning. I really cannot understand what is happening and I use > both predict > and predict.lm but there is no difference. > > Explicitly the code is: > > fe.nox <- lm(nox~ state.1 + state.2 + state.3 + state.4 + state. > 5 + > state.6 + state.7 + state.8 + state.9 + time.1 + time.2 + > time.3 + > time.4 + time.5 + time.6 + time.7 + pcinc + I(pcinc^2) + I > (pcinc^3), > data=ekc) > > p.fe.nox<-predict.lm(fe.nox, new, interval = "prediction", level=0.95, > incl.non.slopes=FALSE) > > Any Help would be highly appreciatedWhere do you get a predict.lm() function that has an argument ``incl.non.slopes''??? Neither the help file nor args(predict.lm) reveal any trace of such an argument. You must be using a modified version of this function. So check with whomever you got it from as to why this argument is not having the effect you expect. It is not at all clear to me what you *do* expect. Are you trying, artificially, to set the intercept to 0 before predicting? Why would you want to do that? Of course you don't get any difference between predict() and predict.lm(). The predict() function is generic, and fe.nox is of class "lm" so the method predict.lm() will be used. I'm sure your data could be structured so that your model could be written with much less verbosity. cheers, Rolf Turner ###################################################################### Attention:\ This e-mail message is privileged and confid...{{dropped:9}}