Note: This exercise is borrowed from Jason Blevins
This is a short exercise in running maximum likelihood estimation (MLE) in R. We will do it for the following AR(1) process: [ z*t = \mu + \rho (z*{t - 1} - \mu) + \sigma \varepsilon_t ] where (\varepsilon_t \sim N(0, 1)).
Before I get into the details of MLE, what is the fundamental insight of MLE? The idea is that we want to estimate the parameters of the model that are generating our data.

Intro State Fines and Forfeits and Parking County Fines and Forfeits and Parking Intro Self-driving cars are a popular topic with futurists making predictions about how they will change cities, work, and our lives. Thousands of lives will be saved because self-driving cars will be much safer than distracted drivers. Parking lots will be demolished as cars can be summoned at will.

Reasons to Use R and RStudio Introduction to Packages data.table Plotly R Markdown Blogdown Reasons to Use R and RStudio R is a universal tool for all parts of research including data cleaning and analysis. However, it also has powerful tools for writing up your research in a reproducible and easily updatable way and generating a personal website to host your research.

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