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, 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: |
10100 Mathematical Sciences (Narrow Grouping) |
HECS Band (if applicable): |
2 |
|
Extent to which this unit or thesis
utilises online information: |
Not Online |
Result Type: |
Grade/Mark |
|
Availability |
| Year |
Location |
Period |
Internal |
Area External |
Central External |
| 2004 |
Bentley Campus |
Semester 2 |
Y |
|
|
Area
External |
refers to external course/units run by the School or Department, offered online or through Web CT, or offered by research. |
Central
External | refers to external course/units run through the Curtin Bentley-based Distance Education Area |
|
