Hi I have a little R problem. I have created a GLM model in R and now I want to predict some values outside the values I have in the model (extrapolate).
I have this code: fitted.model4 <- glm(Yval ~ time, family=gaussian, data=Fuel) The question is - How do I predict a value of Yval ie with a value of time = 340 and also get confidence/prediction intervals for Yvar? I have tried the predict.glm but cannot make it work - any suggestions how to do this using predict.glm? **** Yval are 312 fuel prices ranging from 60 to 140 and time is a sequence from 1 to 312. The GLM summary output is as follows: Deviance Residuals: Min 1Q Median 3Q Max -24.978 -4.033 -0.391 4.747 15.323 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 79.698229 0.871830 91.42 <2e-16 *** seq(1:312) 0.180127 0.004828 37.31 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for gaussian family taken to be 59.00219) Null deviance: 100408 on 311 degrees of freedom Residual deviance: 18291 on 310 degrees of freedom AIC: 2161.6 Number of Fisher Scoring iterations: 2 ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html