Creating function arguments from a named list (with an application to stats4::mle)

Question

I should start by saying what I\'m trying to do: I want to use the mle function without having to re-write my log likelihood function each time I want to try a different model s

Answer 1

You can use the mle2 function from the package bbmle which allows you to pass vectors as parameters. Here is some sample code.

# REDEFINE LOG LIKELIHOOD
ll2 = function(params){
  beta = matrix(NA, nrow = length(params) - 1, ncol = 1)
  beta[,1] = params[-length(params)] 
  sigma    = params[[length(params)]]
  minusll  = -sum(log(dnorm(Y - X %*% beta, 0, sigma)))
  return(minusll)
}

# REGRESS Y ON X1
X <- model.matrix(lm(y ~ x1, data = df))
mle2(ll2, start = c(beta0 = 0.1, beta1 = 0.2, sigma = 1), 
  vecpar = TRUE, parnames = c('beta0', 'beta1', 'sigma'))

# REGRESS Y ON X1 + X2

X <- model.matrix(lm(y ~ x1 + x2, data = df))
mle2(ll2, start = c(beta0 = 0.1, beta1 = 0.2, beta2 = 0.1, sigma = 1), 
      vecpar = TRUE, parnames = c('beta0', 'beta1', 'beta2', 'sigma'))

This gives you

Call:
mle2(minuslogl = ll2, start = c(beta0 = 0.1, beta1 = 0.2, beta2 = 0.1, 
    sigma = 1), vecpar = TRUE, parnames = c("beta0", "beta1", 
    "beta2", "sigma"))

Coefficients:
     beta0      beta1      beta2      sigma 
 0.5526946 -0.2374106  0.1277266  0.2861055