[R] Is AIC in glm right?

[Hiroto Miyoshi]

Could anyone help me?
I am doing a regression analysis using glm.
and the glm function gives AIC at the end of 
the output.  However, the AIC value the function
gives does not seem right.  The details of my 
analysis goes as follows.

 > x
     y  x z
1  325  2 1
2  275  4 0
3  350  4 1
4  400  6 1
5  325  7 0
6  425  8 1
7  375 10 0
8  475 10 1
9  400 12 0
10 575 12 1
11 425 14 0
12 450 16 0
13 700 17 1
14 525 18 0
15 600 20 0
16 750 20 1
17 650 22 0
18 775 23 1
19 675 24 0
20 825 26 1

> glm(x$y~x$x+x$z)

Call:  glm(formula = x$y ~ x$x + x$z) 

Coefficients:
(Intercept)          x$x          x$z  
     148.82        21.85       131.51  

Degrees of Freedom: 19 Total (i.e. Null);  17 Residual
Null Deviance:      533000 
Residual Deviance: 13350        AIC: 194.8 

> a<-residuals(glm(x$y~x$x+x$z))
> sum(a*a)
[1] 13347.96
> 

Now, since sum of squares of residuals of the regression 
is 133347.96, should AIC be 136.068, 
i.e. 20*ln(13348/20)+2*3?

Could someone help me?
Thank you.
---------------------------
Hiroto Miyoshi　（三好弘人）
h_m_ at po.harenet.ne.jp



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