Area: |
Department of Mathematics and Statistics |
Credits: |
25.0 |
Contact Hours: |
3.0 |
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** 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. ** |
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Lecture: |
1 x 3 Hours Weekly |
Anti Requisite(s): |
302387 (v.2) Time Series Modelling 404 or any previous version
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Prerequisite(s): |
302315 (v.2) Mathematical Statistics 202 or any previous version
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Syllabus: |
Exponential smoothing methods to forecast non-seasonal and seasonal time series. Stochastic time series models, Fundamental Concepts. Invertibility & Stationarity, Autocorrelation & 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. |
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** 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. ** |
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Field of Education: |
10100 Mathematical Sciences (Narrow Grouping) |
HECS Band (if applicable): |
2 |
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Extent to which this unit or thesis utilises online information: |
Not Online |
Result Type: |
Grade/Mark |
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Availability |
Year |
Location |
Period |
Internal |
Area External |
Central External |
2004 |
Bentley Campus |
Semester 2 |
Y |
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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 |
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