Dear all, I am a R user since about 3 weeks now and still struggeling with things that must be very easy for you... This week I am struggling with the function predict() I want to use this function to get a 95% interval. I understand that you have to use it in such a way as: lm_examplemodel<- lm(y~x1 + x2 + x3) newdata <- data.frame(x1 = ???, x2 = ???, x3 = ???) predict(lm_examplemodel, newdata, interval = 'confidence') And here comes my questions. As you maybe already have guessed its about the questions marks/ the values for the new data frame you have to use. I read in help(predict.lm) that you have to use a new data frame to be able to use the predict function, but I dont know what values I have to assign to x1 and x2 ... to create the new data set. In the help function it says that you can use the fitted values, but when I use the function: fitted(lm_examplemodel) or fitted.values(lm_examplemodel) I get many many columns. I think that the function gives a fitted value for every Yi and Xi. SO how do I get those values? Do i have to use another function than fitted? Or not the fitted values at all? Thanks already so much! Cheers,maria -- View this message in context: http://r.789695.n4.nabble.com/Using-predicted-in-R-tp3934150p3934150.html Sent from the R help mailing list archive at Nabble.com.
Using predicted() in R
2 messages · flokke, David Winsemius
On Oct 24, 2011, at 2:45 PM, flokke wrote:
Dear all, I am a R user since about 3 weeks now and still struggeling with things that must be very easy for you... This week I am struggling with the function predict() I want to use this function to get a 95% interval. I understand that you have to use it in such a way as: lm_examplemodel<- lm(y~x1 + x2 + x3)
Many times the x1,x2,and x3 will be irregularly spaced.
newdata <- data.frame(x1 = ???, x2 = ???, x3 = ???)
You might want to create predictions on a regular grid for plotting functions htat require such. Obviously you would want to keep the values within the ranges of original values so you don't extrapolate beyond the range of measurements.
predict(lm_examplemodel, newdata, interval = 'confidence')
And you might be plotting the estimated and 95% ranges.
And here comes my questions. As you maybe already have guessed its about the questions marks/ the values for the new data frame you have to use. I read in help(predict.lm) that you have to use a new data frame to be able to use the predict function, but I dont know what values I have to assign to x1 and x2 ... to create the new data set.
Perhaps: x1=seq(range(x1)[1]:range(x1)[2], by=diff(range(x1))/10 ... und so weiter.
In the help function it says that you can use the fitted values, but when I use the function: fitted(lm_examplemodel) or fitted.values(lm_examplemodel) I get many many columns. I think that the function gives a fitted value for every Yi and Xi.
That looks wrong. `fitted` should be one per record. You have not followed the advice to post real data so it is not possible to diagnose your error. Please read the Posting Guide.
SO how do I get those values? Do i have to use another function than fitted? Or not the fitted values at all?
David Winsemius, MD West Hartford, CT