Courses Handbook 2010

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
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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