Hi, I have used the mgcv library to generate a simple additive model. I want to know how to plot the function on the raw data with confidence intervals whan I have TWO variables in the model. I get it to work with one variable but not with two. I am on the limit for what I understand in R, so be gentle. I have read the help file on predict.gam, but did not get any help out of it.
#My model: Model <- gam(var ~ s(var1, k=4) + s(var2, k=4), data = mydata) # Plotting the model: par(mfrow=c(1,1)) plot(Model ) #get a plot of the smoother plot(var ~ var1, data = mydata) #plotting the raw data ##predictions from M1 pred.gam <- predict.gam(M1, se.fit=TRUE, type="response") #Plotting the function and confidence intervals. I <- order(mydata$Ncell) lines(mydata$Ncell[I], pred.gam$fit[I], lwd = 2) lines(mydata$Ncell[I], pred.gam$fit[I] + 2 * pred.gam$se.fit[I], lty = 2, lwd = 2) lines(mydata$Ncell[I], pred.gam$fit[I] - 2 * pred.gam$se.fit[I], lty = 2, lwd = 2) It all works fine if the model instead is: ModelSimple <- gam(var ~ s(var1, k=4), data = mydata) However, I get different results (for obvious reasons) if I predict from Model or ModelSimple. Please, help me!!!! Anna Anna Zakrisson Braeunlich PhD Student Department of Systems Ecology Stockholm University Svante Arrheniusv. 21A SE-106 91 Stockholm E-mail: a...@ecology.su.se Tel work: +46 (0)8 161103 Mobile: +46-(0)700-525015 Web site: http://www.ecology.su.se/staff/personal.asp?id=163 ><((((º>`â¢. . ⢠`â¢. .⢠`â¢. . ><((((º>`â¢. . ⢠`â¢. .⢠`â¢. .><((((º> [[alternative HTML version deleted]]
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