[R] a Question regarding glm for linear regression

[Andra Isan]

Hello All,
I have a question about glm in R. I would like to fit a model with glm function, I have a vector y (size n) which is my response variable and I have matrix X which is by size (n*f) where f is the number of features or columns. I have about 80 features, and when I fit a model using the following formula, 
glmfit = glm(y ~ x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 + x9 + x10 + x11 + x12 + x13 + x14 + x15 + x16 + x17 + x18 + x19 + x20 + x21 + x22 + x23 + x24 + x25 + x26 + x27 + x28 + x29 + x30 + x31 + x32 + x33 + x34 + x35 + x36 + x37 + x38 + x39 + x40 + x41 + x42 + x43 + x44 + x45 + x46 + x47 + x48 + x49 + x50 + x51 + x52 + x53 + x54 + x55 + x56 + x57 + x58 + x59 + x60 + x61 + x62 + x63 + x64 + x65 + x66 + x67 + x68 + x69 + x70 + x71 + x72 + x73 + x74 + x75 + x76 + x77 + x78 + x79 + x80)
it gives me an error "Error in eval(expr, envir, enclos) : object 'x3' not found" which I dont know why I am given those errors. The other thing is that when I use the "glm.fit", I can get coefficients without any errors. So, I am not sure what is going on and if glm.fit is the same as glm, can I use glm.fit instead of glm?

Thanks a lot, 
Andra