A scientist wishes to estimate the proportion $\theta \in(0,1)$ of presence of a gene in a population of flies of size $n$. Every fly receives a chromosome from each of its two parents, each carrying the gene $A$ with probability $(1-\theta)$ or the gene $B$ with probability $\theta$, independently. The scientist can observe if each fly has two copies of the gene A (denoted by AA), two copies of the gene $B$ (denoted by BB) or one of each (denoted by AB). We let $n_{\mathrm{AA}}, n_{\mathrm{BB}}$, and $n_{\mathrm{AB}}$ denote the number of each observation among the $n$ flies.

(a) Give the probability of each observation as a function of $\theta$, denoted by $f(X, \theta)$, for all three values $X=\mathrm{AA}, \mathrm{BB}$, or $\mathrm{AB}$.

(b) For a vector $w=\left(w_{\mathrm{AA}}, w_{\mathrm{BB}}, w_{\mathrm{AB}}\right)$, we let $\hat{\theta}_{w}$ denote the estimator defined by

$$\hat{\theta}_{w}=w_{\mathrm{AA}} \frac{n_{\mathrm{AA}}}{n}+w_{\mathrm{BB}} \frac{n_{\mathrm{BB}}}{n}+w_{\mathrm{AB}} \frac{n_{\mathrm{AB}}}{n} .$$

Find the unique vector $w^{*}$ such that $\hat{\theta}_{w^{*}}$ is unbiased. Show that $\hat{\theta}_{w^{*}}$ is a consistent estimator of $\theta$.

(c) Compute the maximum likelihood estimator of $\theta$ in this model, denoted by $\hat{\theta}_{M L E}$. Find the limiting distribution of $\sqrt{n}\left(\hat{\theta}_{M L E}-\theta\right)$. [You may use results from the course, provided that you state them clearly.]