Let $X$ and $Y$ be two independent random variables with respective pdfs:
$$f \left(x;\theta_i \right) =\begin{cases} \frac{1}{\theta_i} e^{-x/ {\theta_i}} \quad 0<x<\infty, 0<\theta_i< \infty \\ 0 \quad \text{elsewhere} \end{cases} $$
for $i=1,2$. Two indepedent samples are drawn in order to test $H_0: \theta_1 =\theta_2 $ against $H_1 : \theta_1 \neq \theta_2 $ of sizes $n_1$ and $n_2$ from these distributions. I need to show that the LRT $\Lambda$ can be written as a function of a statistic having $F$ distribution, under $H_0$.
Since the mle of this distribution is $\hat{\theta}=\bar{x} $, the LRT statistic becomes (I am skipping a few tedious steps here):
$$ \Lambda =\frac{\bar{x}^{n_1} \bar{y}^{n_2} \left( n_1+n_2 \right)}{n_1 \bar{x}+n_2 \bar{y}}$$
I know that the $F$ distribution is defined as the quotient of two independent chi-square random variables, each one over their respective degrees of freedom. Additionally, since $X_i,Y_i \sim \Gamma \left( 1,\theta_1 \right)$ under the null, then $\sum X_i \sim \Gamma \left(n_1 ,\theta_1 \right)$ and$\sum Y_i \sim \Gamma \left(n_2, \theta_1 \right) $.
But how can I proceed from here? Any hints?
Thank you.