SMART goals from Thursday's Lecture

[timothyhoang]

• know the kind of data format for inputs
• understanding the models
• making graphs dynamic
• figuring out what type of graph would be best (easier to understand, representative of the data)
• facilitate comparisons between models
• communicate with curators and analyzers; know what data to expect
• decide how we want the data formatted and negotiate with DC and analyzers

Note: we agreed to look over the Stark's lecture slides to gain a more complete understanding of the types of visuals that would be meaningful from the analysis and to know the variables we need in our input

[timothyhoang]

Also, try to read and understand the synthesized notes: https://docs.google.com/document/d/1zgaOc7qV4MDRyD3zhKvdBlZq4c6V2zYqP8beQMw22i8/edit

[timothyhoang]

It is helpful to read the Details section (pg. 4-6) for the ETAS R package to understand some of parameters for the ETAS model:
http://cran.r-project.org/web/packages/ETAS/ETAS.pdf

[chocoho]

Thanks for the last link! It's useful