R help - Apr 2015 - optimx: Cannot evaluate function at initial parameters

Hello,I am estimating a system of nonlinear GMM. the following are my objective
function, the gradient function and the optimx code for the optimization. ?I
actually worked out the gradient and hessian by hand before inputing the code
into r. However, I did get the following error message in my optimx routine
objective functionobj = function(initial.values,z) {? e1 = y1-(a1*x1 + a2*x2
+a3*x3 + a4*x4 + a5*x5 + a22*(exp(a6*x6 + a7*x7 + a8*x9 + a9*x10 + a10*x11 +
a11*x12 + a14*x16)/(1+exp(a6*x6 + a7*x7 + a8*x9 + a9*x10 + a10*x11 + a11*x12 +
a14*x16))))?? e2 = y2-(b1*x1 + b2*x2 +b3*x3 + b4*x4 + b5*x5 + b22*(exp(b6*x6 +
b7*x7 + b8*x9 + b9*x10 + b10*x11 + b11*x12 + b14*x16)/(1+exp(b6*x6 + b7*x7 +
b8*x9 + b9*x10 + b10*x11 + b11*x12 + b14*x16))))? e3 = y3-(exp(c1*x1 + c2*x18 +
c3*x19 + c4*x20 + c5*x21 + c6*x14 + c7*x8)/(1 + exp(c1*x1 + c2*x18 + c3*x19 +
c4*x20 + c5*x21 + c6*x14 + c7*x8)))? e = rbind(e1,e2,e3)? q =
t(e)%x%z%x%w%x%t(z)%x%e? return(q)}

gradientgradient = function(initial.values,z) {? df =
2*(t(d)%x%z%x%w%x%t(z)%x%e)? return(df)}

hessian = function(initial.values,z) {? h = 2*(t(d)%x%z%x%w%x%t(z)%x%d)?
return(h)}

nlgmm = optimx(par=initial.values, dat= dta, fn=obj, gr=gradient,hess=hessian,
method = c("BFGS","nlmind","nlm"),
itnmax=c(500,500,500), control=list(maximize=TRUE))Maximizing -- use negfn and
neggrError in optimx.check(par, optcfg$ufn, optcfg$ugr, optcfg$uhess, lower,
?:?? Cannot evaluate function at initial parameters
A way forward will be greatly appreciated.
ThanksOlufemi?

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