If you are taking this course with us, Welcome on board and we hope you'll have a nice journey with us. For immediate questions about this place, contact Mihai or Håvard! This is the place you can find Course Materials, Assignments and Solutions.
- Lecture 1 (Programming and Data Basics) : MC
- Lecture 2 (Simulation Basics and First Monte Carlo) : HH
- Lecture 3 (Hypothesis Testing and Predictive Models) : DR
- Lecture 4 (Logistic Regression and MLE) : HH
- Lecture 5 (Bootstrapping and Simulation of Quantities of Interest) : DR
- Lecture 6 (Multinomial and Ordered and Count Models) : HH
- Lecture 7 (Count and Panel Models) : HH
- Lecture 8 (Tree-based models, Random Forests and Bagging) : MC
- Assignment 1.1 (Data Management) : https://github.com/mihaicroicu/AQM2019/blob/master/assignments/assignment1.1.md
- Assignment 1.2 (First Monte Carlo) : https://github.com/mihaicroicu/AQM2019/blob/master/assignments/assignment1.2.pdf
- Assignment 2 (Logistic Regression and Predictive Techniques) : https://github.com/mihaicroicu/AQM2019/blob/master/assignments/assignment2.pdf
- Assignment 3 (Panels, Count Models and Bootstrapping) : https://github.com/mihaicroicu/AQM2019/blob/master/assignments/Assignment%203.pdf
- Assignment 4 (Random Forests and Forecasting) -- ONLY FOR MA students :
- https://github.com/mihaicroicu/AQM2019/blob/master/assignments/Assignment%204.pdf
- Assignemnt 4 for PhD students consists of an independent project, described by HH via e-mail. Contact him for details, questions or to submit/discuss your proposal.
E-mail these assignments to Mihai, Håvard and David. DO NOT upload them to Studentportalen.
Assignments 1.1 + 1.2 are due APRIL 5th AT 17:00. BOTH PARTS ARE DUE!Assignment 2 is due APRIL 12th AT 17:00Assignment 3 is due APRIL 24th AT 17:00Assignment 4 for MA students is due MAY 3rd AT 17:00. Assignment 4 is only due if you are an MA student.If you are a Ph.D. student, Håvard will need your proposal on or before MAY 1st. Your paper is due MAY 24th.- Feedback was given on the assignments to all students for all assignments. Grades will be reported in the coming weeks.
If you stumbled upon this place by accident, this is the Advanced Quantitative Methods class of 2019 at the Department of Peace and Conflict Research at Uppsala University, Sweden. The course is given by Prof. Håvard Hegre, Mihai Croicu and David Randahl. We cover data management, basics of programming (in R), Monte-Carlo Methods and simulation studies, basics of machine-learning (out of sample partitioing and crossvalidation, performance metrics...), Generalized Linear Models (OLS, Logit, Count...) spanning the inferential, simulation and forecasting paradigms. We will also introduce multi-level modelling and end with decomposition machine-learning methods (trees and random forests). This is the most advanced course offered at the M.A./M.Sc. level in the department, and is open to doctoral students. You are of course free to take a look - and if you want to register, visit UUs page (fees may apply and do note this is a campus course with 100% attendance) : http://www.uu.se/en/admissions/exchange/courses/list/course-description/?kKod=2FK055&typ=1