Charles Annis, P.E. wrote: > How many parameters are you trying to estimate? How many observations do > you have? > > What is wrong is that half of your parameter estimates are statistically > meaningless: > > dd <- data.frame(a=c(1, 2, 3, 4, 5, 6), b=c(3, 5, 6, 7, 9, 10)) > > overparameterized.model <- glm(b~poly(a,3),data=dd) > > summary(overparameterized.model) > > > Coefficients: > Estimate Std. Error t value Pr(>|t|) > > (Intercept) 6.6667 0.1725 38.644 0.000669 *** > > poly(a, 3)1 5.7371 0.4226 13.576 0.005382 ** > > poly(a, 3)2 -0.1091 0.4226 -0.258 0.820395 > > poly(a, 3)3 0.2236 0.4226 0.529 0.649562 > > > > > Charles Annis, P.E. > > [EMAIL PROTECTED] > phone: 561-352-9699 > eFax: 614-455-3265 > http://www.StatisticalEngineering.com > > > -----Original Message----- > From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On > Behalf Of Jarek Jasiewicz > Sent: Saturday, January 12, 2008 11:50 AM > To: [email protected] > Subject: [R] glm expand model to more values > > Hi > > I have the problem with fitting curve to data with lm and glm. When I > use polynominal dependiency, fitted values from model are OK, but I > cannot recive proper values when I use coefficents to caltulate this. > Let me present simple example: > > I have simple data.frame: (dd) > a: 1 2 3 4 5 6 > b: 3 5 6 7 9 10 > > I try to fit it to model: > > model=glm(b~poly(a,3),data=dd) > I have following data fitted to model (as I expected) > > fitted(model) > 1 2 3 4 5 6 > 3.095238 4.738095 6.095238 7.333333 8.619048 10.119048 > > and coef(model) > (Intercept) poly(a, 3)1 poly(a, 3)2 poly(a, 3)3 > 6.6666667 5.7370973 -0.1091089 0.2236068 > > so when I try to expand the model to other data (simple extrapolation), > let say: s=seq(1:10,by=1) > > I do: > extra=sapply(s,function(x) coef(model) %*% x^(0:3)) > and here is result: > [1] 12.51826 19.49328 28.93336 42.18015 60.57528 85.46040 118.17714 > [8] 160.06715 212.47207 276.73354 > > the data form expanding coefs are completly differnd from fitted > > What's going wrong? > > Jarek > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > sorry but I cannot understand. What does it means data are statistically meanningless?
It is examle with very simple data which I use according to simpleR manual example to check why I cannot recive expected result. I need simple model y~x^3+x^2....+z to extrapolate data Jarek ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
