[R] glm fit

[mathallan]

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 =
gaussian(link = "identity"))

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-6.6836  -1.3626  -0.2576   1.2038   8.2480  

Coefficients:
                                Estimate Std. Error      t value   Pr(>|t|)    
(Intercept)                     3.525657   0.436102   8.084 8.18e-16 ***
log(sum)                        0.334288   0.025668  13.024  < 2e-16 ***
as.factor(grp)2               0.434262   0.976240   0.445   0.6565    
as.factor(grp)3               3.666490   1.436471   2.552   0.0107 *  
as.factor(grp)4               0.040782   1.024730   0.040   0.9683    
log(sum):as.factor(grp)2  0.007719   0.061914   0.125   0.9008    
log(sum):as.factor(grp)3 -0.209986   0.091578  -2.293   0.0219 *  
log(sum):as.factor(grp)4  0.059342   0.067320   0.881   0.3781    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

(Dispersion parameter for gaussian family taken to be 3.693731)

    Null deviance: 15839  on 4035  degrees of freedom
Residual deviance: 14878  on 4028  degrees of freedom
AIC: 16737

Number of Fisher Scoring iterations: 2


But i'm not sure what I get out of the summary. What does it tell me?

How should the formula for Y look like, out from the summary? Is it
something like

Y=0.334288*X_sum+0.434262*X_2+  ??


And when I get a expression for Y, what does it tell me? Is it an expected
expression?

Can anyone help me please?

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