About

This is my website for DATA 440 (Agent Based Modelling) coursework.

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Index

1. Getting started with R - this exercise includes basic plotting with Base R and ggplot.
2. Plotting geospatial data - this exercise is focused on reading in shape data using sf and plotting with ggplot.
3. Plotting population data - this exercise works on aggregating population data from a raster to different administrative boundaries.
4. Population description - this exercise is an extension of the previous three exercises, with a more thorough description of the population features of Eswatini.
5. Description of de facto settlements - this exercise works to isolate the populous regions of Mkhiweni, a tinkhundla of the Manzini region, as a way of describing some of the de facto human settlements in Eswatini.
6. Adding road networks and healthcare facilities - this exercise begins to look at additional infrastructure and service elements, serving as the first steps towards quantifying accessibility in Mkhiweni.
7. Data Science Insight 1 - a brief introduction to the Tidyverts, a meta package used for time series analysis and forecasting in R.
8. Project 1 - a write up that summarizes elements from the previous few exercises, providing additional analysis along the way.
9. Project 2 Outline - a short summary of my plans for Project 2.
10. Data Science Insight 2 - a quick look at innovations in Twitter geolocation using CNNs.
11. Project 2 - a write up discussing the methods that were applied to produce a synthetic population for Eswatini.
12. Data Science Insight 3 - a whirlwind tour of GANs, several miscellaneous applications, and advances in applications to geospatial analysis.
13. Data Science Knowledge Creation - a reflection on the themes from this course.
14. Project 3 - a writeup up exploring the gravity model of human migration and its potential uses in predicting agent flows in Eswatini.