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Information
| Unit | INSTITUTE OF NATURAL AND APPLIED SCIENCES |
| STATISTICS (PhD) | |
| Code | ISB528 |
| Name | Time Series Analysis - II |
| Term | 2018-2019 Academic Year |
| Term | Spring |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Belirsiz |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. SELAHATTİN KAÇIRANLAR |
| Course Instructor |
The current term course schedule has not been prepared yet.
|
Course Goal / Objective
The objectives of this course are to do modelling and analysis of time series
Course Content
Vector Autoregression, Bayesian Analysis, The Kalman Filter, Generalized Method of Moments, Processes with Deterministic Time Trends, Univariate Processes with Unit Roots, Unit Roots in Multivariate Time Series, Time Series Models of Heteroskedasticity
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | To learn vector autoregression |
| LO02 | To do bayesian analysis |
| LO03 | To explain the Kalman Filter |
| LO04 | To construct Generalized Method of Moments |
| LO05 | To construct Processes with Deterministic Time Trends |
| LO06 | To explain Univariate Processes with Unit Roots |
| LO07 | To explain Unit Roots in Multivariate Time Series |
| LO08 | To construct Time Series Models of Heteroskedasticity |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Vector Autoregression | Source reading | |
| 2 | Maximum likelihood estimation of Partial Vector Autoregression | Source reading | |
| 3 | Bayesian Analysis | Source reading | |
| 4 | The Kalman Filter | Source reading | |
| 5 | Maximum likelihood estimation of parameters | Source reading | |
| 6 | Generalized Method of Moments (GMM) | Source reading | |
| 7 | Generalized Method of Moments (GMM) | Source reading | |
| 8 | Mid-Term Exam | Review the topics discussed in the lecture notes and sources | |
| 9 | GMM and Maximum likelihood estimation | Source reading | |
| 10 | Processes with Deterministic Time Trends | Source reading | |
| 11 | Univariate Processes with Unit Roots | Source reading | |
| 12 | Univariate Processes with Unit Roots | Source reading | |
| 13 | Unit Roots in Multivariate Time Series | Source reading | |
| 14 | Unit Roots in Multivariate Time Series | Source reading | |
| 15 | Time Series Models of Heteroskedasticity | Source reading | |
| 16 | Term Exams | Review the topics discussed in the lecture notes and sources | |
| 17 | Term Exams | Review the topics discussed in the lecture notes and sources |