[R] glm fit

Hi, I try to ask here, because I hope someone will help me understand this problem- I have fittet a glm in R with the results > glm1 <- > glm(log(claims)~log(sum)*as.factor(grp),family=gaussian(link="identity")) > summary(glm1) Call: glm(formula = log(claims) ~ log(sum) * as.factor(grp), family

Re: [R] Summary help

To glm is glm(log(mydata)~log(max_data)*as.factor(grp),family=Gamma(link="log")) And I was wondering if you can read the scale and shape from summary There a quite a few "gamma models" around, so you should tell us more. glmXXX? lmer? Dieter __ R-

[R] Summary help

Hi, I have fittet a gamma model, and is wondering if I can read the shape and the scale direct from the summary Estimate Std. Errort valuePr(>|t|) (Intercept) 1.612e+00 4.735e-02 34.052 <2e-16 *** myvalue 3.564e-02 2.

[R] Kolmogorov-Smirnov test

I got a distribution function and a empirical distribution function. How do I make to Kolmogorov-Smirnov test in R. Lets call the empirical distribution function >Fn on [0,1] and the distribution function >F on [0,1] ks.test( ) thanks for the help -- View this

Re: [R] Generalized linear models (GLM)

e your course instructor will help with that. > > -- > David Winsemius > On Apr 28, 2009, at 11:34 AM, mathallan wrote: > >> >> Hi >> >> I got a dataset >> >> loss max.loss grp >> 1 10 50 2 >> 2

[R] Generalized linear models (GLM)

Hi I got a dataset loss max.loss grp 1 10 50 2 2 15 33 1 3 18 49 2 4 33 38 1 5 8 50 3 6 19 29 1 7 22 51 4 8 50 50

[R] How to read the summary

How can I from the summary function, decide which glm (fit1, fit2 or fit3) fits to data best? I don't know what to look after, so I would please explain the important output. > fit1 <- glm(Y~X, family=gaussian(link="identity")) > fit2 <- glm(Y~X, family=gaussian(link="log")) > fit3 <- glm(Y~X, fa

Re: [R] Generalized linear models

Thanks for the answer David Sum er the "sum insured" the maximal loss of the company. Claims, is the actually claim size. Group is wich type of business is insured. Can you help me to solve the problem? It is very difficult to determine "rightness" since you have omitted essential backgroun

[R] Generalized linear models

I have to fit a generalized linear model in R, and I have never done this before, so I'm in very much doubt. I have a dataset (of 4036 observations) claims sum grp 1 3852 345702931 2 1194 7776468 1 3