# [R] genralized linear regression - function glm - number of

Christine SINOQUET christine.sinoquet at univ-nantes.fr
Thu Nov 18 17:00:38 CET 2010

```Hello,

Performing a linear regression through the function glm ("yi ~ X\$V1 +
X\$V2 + X\$V3 + X\$V4 + X\$V5 + X\$V6 + X\$V7 + X\$V8 + X\$V9 + X\$V10"), I then
edit the information about the coefficients:

print(coefficients(summary(fit)))

I note that the number of coefficients (7) is lower than the number of
predictors (10).
In this case, I work on simulated data for which I forced yi to be a
linear function of the 10 predictors.

intercept: 0.0180752965003802
predictor 1: -0.0111046268531608
predictor 2: -0.0185366138753851
predictor 3: 0.107341157096227
predictor 4: 0.00162924662836275
predictor 5: 0.00162924629403743
predictor 6: -0.0171999854554059
predictor 7: -0.0171999856835917
predictor 8: -0.057207682945982
predictor 9: -0.0171999856239631
predictor 10: 0.134643228957395

"yi ~ X\$V1 + X\$V2 + X\$V3 + X\$V4 + X\$V5 + X\$V6 + X\$V7 + X\$V8 + X\$V9 + X\$V10"
Estimate   Std. Error       t value Pr(>|t|)
(Intercept)  0.018062134 5.624517e-17  3.211322e+14        0
X\$V1        -0.011104627 3.084989e-17 -3.599567e+14        0
X\$V2        -0.018536614 3.241635e-17 -5.718291e+14        0
X\$V3         0.107341157 4.884358e-17  2.197651e+15        0
X\$V4         0.003258493 3.286878e-17  9.913643e+13        0
X\$V6        -0.051599957 4.203840e-17 -1.227448e+15        0
X\$V8        -0.057207683 3.049835e-17 -1.875763e+15        0
X\$V10        0.134643229 3.849911e-17  3.497308e+15        0

I am sure to have regressed the right number of variables, since I check
that the formula is correct:
"yi ~ X\$V1 + X\$V2 + X\$V3 + X\$V4 + X\$V5 + X\$V6 + X\$V7 + X\$V8 + X\$V9 + X\$V10"

Could somebody explain to me
1) why there are mismatches between the "true" coefficients for
predictors 4 and 6
and
2) why there is no information edited for predictors 5, 7 and 9 ?