Fitting Spatio-Temporal Variogram using WLS

I have been trying to fit a Spatio-Temporal Variogram using non-separable
classes of covariances using the WLS criterion, as described in papers such
as Cressie and Huang(1999), Gneiting (2002). Attached is the .Rda file
which includes a data set named coord.smooth having three variables time
lag, space lag and variogram values. I have plotted a wireframe as well.
But I'm not getting any result using optim() or nls(). Here is the way I'm
using the optim() function for a single parametric model.

weights<-c(with(coord.smooth,table(tlag,slag)))
weights<-weights[-1]
##Cressie Huang (1991)
##Parametric ST variogram Families
weightedLS<-function(par){
  Sigma<-par[1]
  Tau<-par[2]
  a<-par[3]
  b<-par[4]
  n<-weights
  observed<-coord.smooth[,3]
  h<-coord.smooth[,2]
  u<-coord.smooth[,1]
  eg1<-exp(-b^2*h^2/(a^2*u^2+1))/(a^2*u^2+1)
  pred<-Sigma*(1-eg1)+Tau
  wls<-sum(n*(observed/pred)-1)^2
  return(wls)

}

eg1.fit<-optim(c(0,0,0,0),fn=weightedLS,
               method="L-BFGS-B",lower=rep(0,4))
I have obtained the following error:

Error in optim(c(0, 0, 0, 0), fn = weightedLS, method = "L-BFGS-B", lower
= rep(0,  :
  L-BFGS-B needs finite values of 'fn'