I am trying to run a nested optimization routine for Empirical Likelihood with the following routine (where I am implementing a mini-max optimization routine over the function f = ln(1+lambda*g(b)), where g(b) are the moment conditions). Thus there are two sets of parameters, lambda (1 x cols(z)) and beta (1 x cols(x)). However it gives an error at the end stating 'starting values for parameters required', despite providing the starting values below. Any help would be highly appreciated,

mata:
void lambda1(todo,lambda,beta,f,S1,H)
{
real colvector y
real matrix z, x
u = y-x*beta'
m= z:*u
g = m*lambda'
f = mean(ln(1:/(1:+g)))
if (todo>=1){
S1 = -mean(m:/(1:+g))
}
}
real scalar function invda(real rowvector beta)
{
I=optimize_init()
optimize_init_evaluator(I,&lambda1())
optimize_init_evaluatortype(I,"d1")
optimize_init_params(I,J(1,cols(H),0))
optimize_init_argument(I,1,beta)
optimize_init_which(I,"max")
optimize_init_conv_maxiter(I,10000)
optimize_init_singularHmethod(I,"hybrid")
lambda=optimize(I)
a = optimize_result_value(I)
return(lambda)
}

void beta1(todo,beta,f,S2,H)
{
real colvector y
real matrix z, x
real rowvector lambda
lambda=invda(beta)
m= z:*u
g = m*lambda'
f = mean(ln(1:/(1:+g)))
if (todo>=1){
Q2 = mean(((z:*x[,1])*lambda'):/(1:+g))
Q3 = mean(((z:*x[,2])*lambda'):/(1:+g))
Q4 = mean(((z:*x[,3])*lambda'):/(1:+g))
Q5 = mean(((z:*x[,4])*lambda'):/(1:+g))
Q6 = mean(((z:*x[,5])*lambda'):/(1:+g))
S2 = Q2,Q3,Q4,Q5,Q6
}
}
S=optimize_init()
optimize_init_evaluator(S,&beta1())
optimize_init_evaluatortype(S,"d1")
optimize_init_params(S,(b0))
optimize_init_which(S,"min")
optimize_init_technique(S, "nr")
optimize_init_conv_maxiter(S,10000)
optimize_init_singularHmethod(S,"hybrid")
q=optimize(S)
q
end