Convergence of fixed point iteration for polynomial equations 
I'm looking for the solution $x$ of
$$x^n+nx-n=0.$$

Thoughts: From graphing it for several $n$ it seems there is always a solution in the interval $[\tfrac{1}{2},1)$. For $n=1$, the solution is the fraction $\tfrac{1}{2}$ and for higher $n$, the solution shifts to the right.
I then saw that the equation reads $$F_n(x)=x$$ with
$$F:[0,1]\to[0,1],\ \ \ \ \ \ F_n(x):=1-\frac{x^n}{n}.$$
I think I got all conditions together for making the iteration of $F_n$'s the general soluton for the equation. I computed $$x_5=F_5(F_5(F_5(F_5(F_5(F_5(F_5(F_5(x_S)))))))),$$
with starting value $x_S=\tfrac{1}{2}$ and it seems to be the solution of the equation for $n=5$.
Related wikipedia links: Fixed point theorem, Banach fixed-point theorem, Fixed point iteration;
I wonder:

Have I found the soluton and can one evaluate the iteration to a closed form?

Might be that it involves polylogs. edit: At least Wolfram Alpha claims to know $$n(x)=W\left(\frac{-\log(x)}{x-1}\right)/\log(x),$$ even if $n(x)$ isn't too interesting.

In my case, how is the relation between the function $x(n)$ and (I think) the fixed point combinator for the iteration?
Does it matter what I choose for $x_S$ here? Can one relate it's value and the number for necessary iteration for a good agreement with the real value?

(Also, are there any results on which polynomial equations this technique works? The property $F:[0,1]\to[0,1]$ seemed accidental to me.)
 A: You can get a good approximation of the solution as $n \to \infty$ by supposing that $x$ can be written as an asymptotic series in powers of $1/n$, say
$$
x \sim 1 + \sum_{k=1}^{\infty} \frac{a_k}{n^k},
$$
then substituting this into the given equation and calculating the coefficients recursively.  For example we can calculate $a_1$ and $a_2$ by writing
$$
\begin{align*}
0 &\approx \left(1 + \frac{a_1}{n} + \frac{a_2}{n^2}\right)^n + n\left(1+\frac{a_1}{n} + \frac{a_2}{n^2}\right) - n \\
&= \left(1 + \frac{a_1}{n} + \frac{a_2}{n^2}\right)^n + a_1 + \frac{a_2}{n} \\
&= a_1 + e^{a_1} + \frac{2a_2 (1+e^{a_1}) - a_1^2 e^{a_1}}{2n} + O\left(\frac{1}{n^2}\right).
\end{align*}
$$
By sending $n \to \infty$ we get that $a_1 + e^{a_1} = 0$ and so
$$
a_1 = -W(1),
$$
where $W$ is the Lambert W function.
Then, setting the coefficient of $1/n$ to $0$ and substituting the above value of $a_1$ we find that
$$
a_2 = \frac{W(1)^3}{2(1+W(1))}.
$$
Thus we have
$$
x \approx 1 - W(1) n^{-1} + \frac{W(1)^3}{2(1+W(1))} n^{-2}.
$$
This approximation seems to be pretty good.  Below is a plot which compares the numerical roots with the asymptotic formula for $1 \leq n \leq 10$.

This series might actually converge for large enough $n$ but I don't see how to prove it.  If the implicit function theorem could be employed then you would be set.
A: Isn't this simply the result of the Banach fixed-point theorem?
In you case one must prove that there exists $q$ such that:
$$d(F_n(x),F_n(y))=\frac{|y^n-x^n|}{n} \le q |x-y|$$
Which is true for all $n>1, x>0$, with say, $q=0.9$, So that it doesn't matter what $x_S$ you choose. 
Regarding a closed form - convergence of an iterative series says nothing about the existence of such a closed form solution.
