predict.glm - how to?

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predict.glm - how to?

 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 ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide! http://www.R-project.org/posting-guide.html