Thank you!

Here is the simple function to perform Wald test for nonlinear restrictions
in an ols model (the question is below)

# powers to pass to fdjac  p(x) is x   p(x,3) is x^3

function scalar p(scalar x, scalar p[1])
    return x^p
end function


function matrix fun4(strings fun, matrix rhs, matrix beta, matrix vcov, scalar s, scalar df)
    b = beta
    coll = rows(b)
    r = nelem(fun)
    matrix matr = zeros(r,coll)
    matrix matr2 = zeros(r,1)
    loop i=1..r --quiet
        fu = fun[i]
        vect = fdjac(b,@fu)
        matr[i,] = vect
        matr2[i,] = @fu-rhs[i]
    endloop
    ret = matr*vcov*transp(matr)
    reti = inv(ret)
    ff = transp(matr2)*reti*matr2/r
    pval = 1-cdf(F,r,df,ff)
    out = {ff,pval}
    colnames(out, "F p-value")

    return out

end function

## examples of restrictions
matrix rhs = {0,0,0}
strings S = array(2)

S[1] = "p(b[2])+p(b[3])"
S[2] = "p(b[2])+2*p(b[3])"

strings S1 = array(1)

S1[1] = "p(b[2])+p(b[3])"

open denmark.gdt

ols LRM const LRY IBO


eval fun4(S1,rhs,$coeff,$vcv,$sigma,$df)

eval fun4(S,rhs,$coeff,$vcv,$sigma.$df)

Is there any way to make $coeff,$vcv,$sigma,$df the defaults so that
the call be fun4(S1,rhs)?