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 =
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
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
__
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
--
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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,
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
AM, mathallan wrote:
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
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 background
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
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