Advanced Predictive Analytics
Exam number: 6810
Semester: from 1st semester
Duration of the module: One semester
Form of the module (i.e. obligatory, elective etc.): Elective
Frequency of module offer: Summer semester 2019
Applicability of module for other study programmes:
Obligatory or elective in other study programmes. For further information check regulations of the study programme.
Person responsible for module: Prof. Dr. Sven Müller
Name of the professor: Prof. Dr. Sven Müller
Language of teaching: English
ECTS-Credits (based on the workload): 6
Workload and its composition (self-study, contact time):
Contact time (Lecture, tutorial etc.): 30 h; self-study: 150 h
Contact hours (per week in semester): 2
Methods and duration of examination:
Emphasis of the grade for the final grade: Please check regulations of the study programme
Aim of the module (expected learning outcomes and competencies to be acquired):
Contents of the module:
This course continues the learning of discrete choice models introduced in the course "Predictive Analytics". In particular, we focus on models and algorithms that improve the predictive quality of classic discrete choice models. For example, nested, cross-nested logit models, MEV models, probit models, and mixed logit. Further, we discuss how attitudes, perceptions etc impact the choice behavior of individuals and how we can account for these in modern (hybrid) choice models.
Teaching and learning methods:
Literature (compulsory reading, recommended literature):
Registration in Moodle Viadrina required.