Courses Handbook 2006 - [Archived]

302387 (v.2) Time Series Modelling 404


Area:

Department of Mathematics and Statistics

Credits:

25.0

Contact Hours:

3.0
 
** The tuition pattern below provides details of the types of classes and their duration. This is to be used as a guide only. For more precise information please check your unit outline. **
 

Lecture:

3 x 1 Hours Weekly

Anti Requisite(s):

304193 (v.3) Time Series Modelling 504 or any previous version

Prerequisite(s):

302315 (v.2) Mathematical Statistics 202 or any previous version
 

Syllabus:

Exponential smoothing methods to forecast non-seasonal and seasonal time series. Stochastic time series models and fundamental concepts. Invertibility and stationarity, autocorrelation and partial autocorrelation, identification and estimation in non-seasonal ARIMA models, forecasting and diagnostic checking. Seasonal time series models. Intervention analysis and outlier detection. Multivariate time series, vector ARMA and state-space modelling.
 
** To ensure that the most up-to-date information about unit references, texts and outcomes appears, they will be provided in your unit outline prior to commencement. **
 

Field of Education:

010101 Mathematics

Funding Cluster:

04 - Mathematics, Statistics

SOLT (Online) Definitions*:

Not Online
*Extent to which this unit or thesis utilises online information

Result Type:

Grade/Mark

Availability

Availability Information has not been provided by the respective School or Area. Prospective students should contact the School or Area listed above for further information.

 
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