---
title: "Recitation 4 Note"
author: "Yiming Gong"
date: "2021-07-27T02:07:51Z"
link: "https://bookdown.org/yg484/rec_4_note/"
length_weight: "2.7%"
pinned: false
---

This is the class note for recitation 4. [...] Method of moments estimation is based solely on the law of large numbers, which we repeat here: Let \(M_1, M_2,...\) be independent random variables having a common distribution possessing a mean \(\mu_M\). Then the sample means converge to the distributional mean as the number of observations increase. \[
\bar{M}_n = \frac{1}{n}\sum_{i=1}^n M_i \rightarrow \mu_M \text{, as } n \rightarrow\infty \] To show how the method of moments determines an estimator, we first consider the case of one parameter. We start with independent random variables ...
