Prove that $$\sum_{n=1}^{\infty} \frac{x^n \log(n!)}{n!} \sim x \log(x) e^x \,\,\,\text{as}\,\,\, x \to \infty$$ and $$\sum_{n=1}^{\infty} \frac{(-x)^n \log(n!)}{n!} \to 0 \,\,\,\text{as}\,\,\, x \to \infty$$ This question is related to my previous question. My heuristic approach is that the sum's major contribution comes from $n\approx x$ term, so
$$\sum_{n=1}^{\infty} \frac{x^n \log(n!)}{n!} \sim \frac{x^x\log(x!)}{x!}$$ but using the Stirling formula twice leads to $$\sum_{n=1}^{\infty} \frac{x^n \log(n!)}{n!} \sim \frac{\sqrt{x}\log(x)}{\sqrt{2\pi}}e^x$$ But this reasoning is flawed and I believe I should not ignore all the other terms. (Which I believe to account for $\sqrt{2\pi x}$factor) What kind of approach may give the wanted asymptotic behavior? Any kind of hint is welcome.
I will try to show the first asymptotics.
We begin with the following quantitative form of Stirling's formula:
Now let $N_t$ be a Poisson random variable of rate $t$. Then
\begin{align*} \smash[b]{\sum_{n=0}^{\infty} \frac{t^n \log (n!)}{n!}e^{-t}} &= \Bbb{E}[\log (N_t !)] \\ &= \Bbb{E}[N_t \log (N_t) + \tfrac{1}{2}\log (N_t + 1) - N_t + \mathcal{O}(1)] \\ &= \Bbb{E}[N_t \log (N_t + 1)] + \tfrac{1}{2}\Bbb{E}[\log(N_t + 1)] - t + \mathcal{O}(1). \tag{2} \end{align*}
Now we claim the following:
Assuming this claim, we easily find that
$$ \Bbb{E}[N_t \log(N_t + 1)] = t \log t + \mathcal{O}(1) \quad \text{and} \quad \Bbb{E}[\log(N_t + 1)] = \log t + \mathcal{O}(t^{-1}). $$
Plugging this to $\text{(2)}$ gives
$$ \sum_{n=0}^{\infty} \frac{t^n \log (n!)}{n!}e^{-t} = (t + \tfrac{1}{2})\log t - t + \mathcal{O}(1) = \log (t!) + \mathcal{O}(1). $$
Dividing both sides by $t \log t$ yields the first asymptotics.
Proof of Claim. The last inequality of $\text{(3)}$ is easy to prove. Since the function $x \mapsto \log(x+a+1)$ is concave, by the Jensen's inequality we have
$$ \Bbb{E}[\log(N_t + a + 1)] \leq \log(\Bbb{E} N_t + a + 1) = \log(t+a+1). $$
In order to show the first inequality of $\text{(3)}$, notice that $x \mapsto x\log(x+a)$ is convex (with the 2nd derivative $(2a+x)/(a+x)^2 > 0$). Thus by the Jensen's inequality again
$$ \Bbb{E}[N_t \log (N_t + a)] \geq (\Bbb{E}N_t) \log (\Bbb{E}N_t + a) = t \log(t+a). $$
Finally, the middle equality of $\text{(3)}$ is given by
\begin{align*} \Bbb{E}[N_t \log (N_t + a)] &= \sum_{n=1}^{\infty} n \log(n+a) \cdot \frac{t^n}{n!}e^{-t} \\ &= \sum_{n=0}^{\infty} \log(n+a+1) \cdot \frac{t^{n+1}}{n!}e^{-t} = t \Bbb{E}[\log (N_t + a + 1)]. \end{align*}