Trying to write a linear regression using MLE and optim()

I wrote this:

# Setup problem
x <- runif(100)
y <- 2 + 3*x + rnorm(100)
X <- cbind(1, x)

# True OLS --
lm(y ~ x)

# OLS likelihood function --
ols.lf <- function(theta, K, y, X) {
 beta <- theta[1:K]
 sigma <- exp(theta[K+1])
 e <- (y - X%*%beta)/sigma
 logl <- sum(log(dnorm(e)))
 return(logl)
}

optim(c(2,3,0), ols.lf, gr=NULL,
     method="BFGS", lower=-Inf, upper=Inf,
     control=list(trace=2, fnscale=-1),
     # Now for the "..." stuff
     K, y, X)

I get:

Error in fn(par, ...) : argument "X" is missing, with no default
In addition: Warning message:
numerical expression has 100 elements: only the first used in: 1:K
Execution halted

If someone can show me the way, it'll be most appreciated. :-)