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| MATH0221-3 | Analysis of time series
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| Duration : | 30h Th, 10h Pr, 20h Mon. WS |
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| Credits/ECTS : |
| Master in Economical Sciences, in-depth approach, 2nd year | | Toute l'année | | 5 |
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| Master in Statistics : Biostatistics, professional focus , 2nd year | | Second semester | | 6 |
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| Master in Mathematical Sciences, in-depth approach, 1st year | | Toute l'année | | 8 |
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| Master in Mathematical Sciences, didactic approach, 1st year | | Toute l'année | | 8 |
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| Master in Mathematical Sciences, professional focus in management, 1st year | | Toute l'année | | 8 |
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| Master in Mathematical Sciences, professional focus in computer science, 1st year | | Toute l'année | | 8 |
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| Master in Mathematical Sciences, specialized approach, 1st year | | Toute l'année | | 8 |
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| Master in Statistics : General, Professional focus, 2nd year | | Toute l'année | | 6 |
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| Master in Mathematical Sciences | | Toute l'année | | 8 |
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| Holder(s) : | Paul Gérard |
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| Language : | French language |
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| Course contents : | 1. Modelisation using regression methods: decomposition into trend, seasonal component and perturbation. Detecting outlyers, forcasting.
2. Moving averages: properties and construction. Usual moving averages: arithmetic, Henderdon, Spencer,...
3. Exponential smoothing, Brown's methods, Holt&Winters methods.
4.Theory of stationary processes: stationarity, autocorrelation, partial autocorrelation, spectral analysis, ARMA, ARIMA and SARIMA processes. |
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| Course objective : | Learning to analyse a time series using exploratory and modelling methods. Estimating its trend and seasonal components. Building and fitting ARIMA models. Making prediction. Estimating and using the power spectrum. |
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| Prerequisites : | A course on statistical inference and linear models.
For example: math0210-1 and math 213-1 |
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| Workshops : | Analysis time series with the methods presented during the course.
Introduction to the use of a statistical software on time series (Statistica). |
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| Organization : | Lectures and homeworks.
Practical examples are treated during the lectures. |
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| Written notes : | Handout based on transparencies.
Suggested reading:
1.Séries temporelles et modèles dynamiques. Christian Gourieroux et Alain Monfort. Economica, Collection " Economie et statistiques avancées ".
2.Time series : a biostatistical introduction. P.J.Diggle. Oxford statistical science series. Oxford University Press.
3.Practical time series. Gareth Janack. Arnold. |
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| Assessment : | Oral evaluation and homeworks |
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| Contacts : | Paul GERARD, Institut de Mathématique, Bât.B37, Grande Traverse 12, 4000-Liège
(Sart Tilman),Tel. 00-32-(0)4366.93.84, Fax : 00-32-(0)4366.95.47,
e-mail : paul.gerard@ulg.ac.be |
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