Hi,
I'm trying to use gmm package in order to calculate linear regression (I
need to use the gmm for other application and this is a prior test I'm
doing).
I've defined a function for linear regression with 2 variables (x[,1] holds
the y values, while x[,2:3] holds the x values):
function(tet, x)
{
m1 <- (x[,1] - (tet[1] + tet[2] * x[,2] + tet[3] * x[,3])) * x[,2]
m2 <- (x[,1] - (tet[1] + tet[2] * x[,2] + tet[3] * x[,3])) * x[,3]
m3 <- (x[,1] - (tet[1] + tet[2] * x[,2] + tet[3] * x[,3])) * 1.0
f <-cbind(m1, m2, m3)
return(f)
}
Then I run:
gmm(g1, d, c(0,0,0))
* d - input data.frame
and I get:
Theta[1] Theta[2] Theta[3]
0.055635 0.025520 0.047638
However when I use:
glm(y~x1 + x2, data =d)
I get:
Coefficients:
(Intercept) x1 x2
-0.2833 0.0318 0.6612
When I tries to use the output from glm as initial values to the gmm I got
the following results:
Theta[1] Theta[2] Theta[3]
-0.283349 0.031798 0.661225
In addition when I'm trying the coefficients from the glm run in g1 I get
the minimum result (much smaller results relative to the gmm result).
BTW, d is:
y x1 x2
1 0 1 0.29944294
2 0 2 0.12521669
3 1 3 0.97254701
4 0 4 0.79952796
5 0 5 0.77358425
6 0 6 0.09983754
7 1 7 0.46133893
8 0 8 0.59833493
9 0 9 0.80005524
10 0 10 0.02979412
11 1 11 0.70576655
12 0 12 0.67138962
13 0 13 0.33446510
14 1 14 0.72187427
15 0 15 0.28193852
16 1 16 0.11258881
17 0 17 0.22001868
18 1 18 0.54681964
19 0 19 0.03336023
20 1 20 0.47007378
Can someone explain what am I doing wrong and why I don't get the same
results?
Thanks!
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