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Information
| Code | TS539 |
| Name | Applied Time Series Analysis |
| Term | 2023-2024 Academic Year |
| Semester | . Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. MAHMUT ÇETİN |
Course Goal / Objective
Objectives of this course are three-fold: a) to acquire skills on time series modelling issue, b) to model hydrologic and hydrometeorological time series, c) to interpret the results in depth.
Course Content
Definitions, terms and notations. Elementary statistical principles in time series analysis. Step-by-step sequential analysis of structural characteristics: Tendency, intermittency, periodicity, and stochasticity. Trend analysis. Estimation of periodic parameters by Fourier analysis. Removing trend and periodic component from stochastic process. Time dependence structure: Autocorrelation and partial autoorrelation function for lag k. Spectral analysis. Autoregressive modelling (AR(p)) with constant and/or periodic parameters: Preliminary analysis and model identification, the principle of parsimony in parameters, parameter estimation, goodness-of-fit tests for selected model. Reliability of model parameters. Random number generators and synthetic data generation. Simple ARIMA modelling of time series: Parameter estimation, goodness of fit tests and synthetic data generation.
Course Precondition
In order to enroll this course, it is sufficient to be a graduate or doctoral student. There are no other prerequisites.
Resources
1. Kottegoda, N. T., 1980. Stochastic Water Resources Technology. Department of Civil Engineering, University of Birmingham, UK, Softcover ISBN: 978-1-349-03469-7, eBook ISBN: 978-1-349-03467-3, DOI: https://doi.org/10.1007/978-1-349-03467-3. 2. Machiwal, D., Jha, M., K., 2012. Hydrologic Time Series Analysis. DOI: https://doi.org/10.1007/978-94-007-1861-6, pp. 280, eBook ISBN: 978-94-007-1861-6. 3. Salas, J. D., Delleur, J. W., Yevjevich, V., Lane, W. L., 1997. Applied Modelling of Hydrologic Time Series. Water research publication, Littleton, CO, USA.
Notes
Publications such as scientific articles, MSc or PhD theses, reports, etc. written by using hydrologic and hydro-meterologic time series.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Learns time series concept comprehensively. |
| LO02 | Models Mathematically the structural behavior of time series. |
| LO03 | Interprets stochastic process and their autocorrelation structures. |
| LO04 | Gains the ability to generate synthetic time series from different models by applying goodness-of-fit tests for the model. |
| LO05 | Constructs the integrated time series model integrally by modeling the time series components seperately. |
| LO06 | Gains the ability to model the structural behavior of time series mathematically. |
| LO07 | Interprets the coefficients in the mathematical models of time series. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Has the ability to develop and deepen the level of expertise degree qualifications based on the knowledge acquired in the field of agriculture and irrigation structures | 3 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Has the ability to understand the interaction between irrigation and agricultural structures and related disciplines | |
| PLO03 | Bilgi - Kuramsal, Olgusal | Qualified in devising projects in agricultural structures and irrigation systems. | 1 |
| PLO04 | Bilgi - Kuramsal, Olgusal | Conducts land applications,supervises them and assures of development | |
| PLO05 | Bilgi - Kuramsal, Olgusal | Has the ability to support his specilist knowledge with qualitative and quantitative data. Can work in different disciplines. | 2 |
| PLO06 | Bilgi - Kuramsal, Olgusal | Solves problems by establishing cause and effect relationship | 4 |
| PLO07 | Bilgi - Kuramsal, Olgusal | Has the ability to apply theoretical and practical knowledge in the field of agricultural structures and irrigation department | 5 |
| PLO08 | Bilgi - Kuramsal, Olgusal | Able to carry out a study independently on a subject. | |
| PLO09 | Bilgi - Kuramsal, Olgusal | Has the ability to design and apply analytical, modelling and experimental researches, to analyze and interpret complex issues occuring in these processes. | |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Can access resources on his speciality, makes good use of them and updates his knowledge constantly. | 3 |
| PLO11 | Yetkinlikler - Öğrenme Yetkinliği | Has the ability to use computer software in agricultural structures and irrigation; can use informatics and communications technology at an advanced level. | 5 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Time series and process concept, basic definitions, notations | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 2 | Important remindings on statistical inference, descriptive statistics, and interpretation of statistics | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 3 | Pre-statistical analyssi in time series modelling issue | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 4 | Structural behaviors of time series: Trend, intermittency, periodicity and stocasticity | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 5 | Applications of trend, intermittency, periodicity and stocasticity to real time series data sets. | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | Öğretim Yöntemleri: Anlatım, Proje Temelli Öğrenme |
| 6 | Diognising trend component and its modelling | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 7 | Analysis of periodic component: Fourier approach | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | Öğretim Yöntemleri: Anlatım, Tartışma, Alıştırma ve Uygulama |
| 8 | Mid-Term Exam | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Removing trend and periodicity from experimental data | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
| 10 | Stochastic process and and serial dependency: Lag concept, ACF, PACF, spectral analysis | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | Öğretim Yöntemleri: Anlatım, Tartışma |
| 11 | Application of lag concept, ACF, PACF, spectral analysis to real hydrologic and hydro-meteorologic data sets. | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | Öğretim Yöntemleri: Tartışma, Proje Temelli Öğrenme , Soru-Cevap |
| 12 | AR(p) models with constant and periodical parameters: Model description, principles of parsimony in parametes, parameter estimation | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 13 | AR(p) and ARIMA (p,q) autoregressive models with periodic parameters: Model definition, parsimony principle in model parameter count, parameter estimation | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 14 | Model parameters and confidence tests: Random number generation techniques, AR(p) models, parameter estimation and goodnes-of-fit tests. | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 15 | Synthetic data generation with integrated models: Up-to-date practices | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | Öğretim Yöntemleri: Tartışma, Proje Temelli Öğrenme |
| 16 | Term Exam | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | Ölçme Yöntemleri: Yazılı Sınav, Proje / Tasarım |
| 17 | Term Exams | Studying in detail the relevant chapters in different sources such as books, reports or scientific papers; reviewing and reading articles related to the subject from scientific journals | Ölçme Yöntemleri: Yazılı Sınav, Proje / Tasarım |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||