Let equation $x^n+x=1$ have positive root $a_{n}$.
Show that $$\lim_{n\to \infty}\frac{n}{\ln{(\ln{n}})}\left(1-a_{n}-\dfrac{n}{\ln{n}}\right)=-1$$
some hours ago,it prove that $$\lim_{n\to \infty}\frac{n}{\ln{n}}(1-a_{n})=1$$
How prove this limit $\displaystyle\lim_{n\to \infty}\frac{n}{\ln{n}}(1-a_{n})=1$
this problem is from china paper(1993):http://www.cnki.com.cn/Article/CJFDTotal-YEKJ199301013.htm
and this paper poof is very ugly,so I want see other nice methods,I kown these can use Incremental estimation analysis,Thank you
Let's first set $x = 1 - y$, so that we're looking for the positive zero of
$$ p(y) = (1-y)^n - y. $$
We know from your previous questions that $y \sim \frac{\log n}{n}$ as $n \to \infty$, so that
$$ \begin{align} (1-y)^n &= \exp\left[n \log(1-y)\right] \\ &= \exp\left[-ny + O\left(\frac{(\log n)^2}{n}\right)\right] \\ &= e^{-ny} \left[1 + O\left(\frac{(\log n)^2}{n}\right)\right]. \tag{1} \end{align} $$
We conclude from this that $e^{ny}(1-y)^n$ is almost $1$ when $n$ is large, so we might guess that the solution of the equation
$$ (1-y)^n - y = 0 $$
behaves a lot like the solution of the equation
$$ e^{-ny} - y = 0 \tag{2} $$
when $n$ is large. In fact $(2)$ has an explicit solution in terms of the Lambert $W$ function: $y = W(n)/n$, and this is approximately $\log(n)/n - \log\log(n)/n$. Now let's try to quantify what "behaves a lot like" means in this particular instance.
The equation
$$ \lambda e^{-ny} - y = 0 $$
has a solution
$$ y = \frac{W(\lambda n)}{n}, $$
so by taking $\lambda = e^{ny}(1-y)^n$ we see that the equation
$$ e^{-ny}\Bigl[e^{ny}(1-y)^n\Bigr] - y = 0 $$
has an implicit solution
$$ y = \frac{W\Bigl[n e^{ny}(1-y)^n\Bigr]}{n}. \tag{3} $$
We'll need two facts here. First, it is a consequence of $(1)$ that
$$ n e^{ny}(1-y)^n = n + O(\log n)^2. $$
Second, it is a consequence of my answer here that
$$ W(x) = \log x - \log\log x + O\left(\frac{\log\log x}{\log x}\right) \tag{4} $$
as $x \to \infty$. It follows that
$$ \begin{align} &W\Bigl[n e^{ny}(1-y)^n\Bigr] \\ &\quad= W\Bigl[n + O(\log n)^2\Bigr] \\ &\quad= \log\Bigl[n + O(\log n)^2\Bigr] - \log\log\Bigl[n + O(\log n)^2\Bigr] + O\left(\frac{\log\log\Bigl[n + O(\log n)^2\Bigr]}{\log\Bigl[n + O(\log n)^2\Bigr]}\right). \end{align} $$
We calculate
$$ \begin{align} \log\Bigl[n + O(\log n)^2\Bigr] &= \log n + \log\left[1 + O\left(\frac{(\log n)^2}{n}\right)\right] \\ &= \log n + O\left(\frac{(\log n)^2}{n}\right) \end{align} $$
and similarly
$$ \log\log\Bigl[n + O(\log n)^2\Bigr] = \log\log n + O\left(\frac{\log n}{n}\right), $$
so that
$$ W\Bigl[n e^{ny}(1-y)^n\Bigr] = \log n - \log\log n + O\left(\frac{\log\log n}{\log n}\right). $$
Substituting this into $(3)$ yields
$$ y = \frac{\log n}{n} - \frac{\log\log n}{n} + O\left(\frac{\log\log n}{n\log n}\right), $$
so that
$$ a_n = 1 - \frac{\log n}{n} + \frac{\log\log n}{n} + O\left(\frac{\log\log n}{n\log n}\right). $$
We can rearrange this to see that
$$ \frac{n}{\log\log n}\left(1 - a_n - \frac{\log n}{n}\right) = -1 + O\left(\frac{1}{\log n}\right). $$
In fact it can be shown that $W\Bigl[n + O(\log n)^2\Bigr]$ shares the same asymptotic expansion with $W(n)$, and we can therefore find as many terms as we like of the asymptotic expansion for $a_n$. For example,
$$ a_n = 1 - \frac{1}{n}\left(L_1 - L_2 + \frac{L_2}{L_1} + \frac{(-2 + L_2)L_2}{L_1^2} + O\left(\frac{L_2}{L_1}\right)^3\right) $$
as $n \to \infty$, where $L_1 = \log n$ and $L_2 = \log\log n$. (See equation (15) in this MathWorld article.)