From: Gesmann, Markus <Markus.Gesmann_at_lloyds.com>

Date: Tue 31 May 2005 - 23:54:40 EST

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R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Wed Jun 01 00:05:25 2005

Date: Tue 31 May 2005 - 23:54:40 EST

It appears that you try to do some insurance reserving analysis.
Have a look at http://finzi.psych.upenn.edu/R/Rhelp02a/archive/15315.html, this might be helpful.

Regards

Markus

-----Original Message-----

From: r-help-bounces@stat.math.ethz.ch [mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of Laetitia Mestdagh
Sent: 31 May 2005 14:44

To: r-help@stat.math.ethz.ch

Subject: [R] GLM question

I am unfamiliar with R and I'm trying to do few statistical things like GLM and GAM with it. I hope my following questions will be clear enough:

My datas ( y(i,j ))are run off triangles for example :

J=1

J=2

J=3

I=1

1

2

3

I=2

4

5

I=3

6

My model is :

E[y(i,j)] =m(i,j)

Var[y(i,j)] =constant *m(i,j)

Log(m(i,j)) = eta (i,j)

eta (i,j) = c + alpha(i) + beta(j)

The y(i,j) are the response and they have no specified distribution.

Here is what I did and I'm not getting the right results:

> C<-matrix(nrow = 6, ncol = 5, byrow= TRUE)

*> C[1,]<-y1
*

*> C[2,]<-y2
*

*> C[3,]<-y3
*

*> C[4,]<-y4
*

*> C[5,]<-y5
*

*> C[6,]<-x6
*

> Cdata<-data.frame(C[,1],C[,2],C[,3],C[,4],C[,5])

>fmp<-glm(m~C,family = quasipoisson(link = log),data=Cdata)

1 2 3 4 5 6

1.25 1.75 3.00 3.75 5.25 6.00

So my question are : - Why are the fitted wrong (except for 3 and 6)?

- Is the quasipoisson the right family for my model?

I am a little bit lost and not an expert of R, so I thank in advance for any kind of advice

Laetitia

ils, photos et vidéos !

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Wed Jun 01 00:05:25 2005

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