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TIME SERIES (R)

Module code: ST836
Credits: 5
Semester: 2
Quota: Restricted entry, contact department for details before registering
Department: MATHEMATICS AND STATISTICS
International:

	Overview
	Overview -------- The stationarity of time series models. The forecaster's toolbox. Judgmental forecasts. Regression. Time series decomposition. Exponential smoothing. ARIMA models. Advanced forecasting methods. Using software such as R for forecasting. Lectures and tutorials as for ST306.

	Learning Outcomes
	On successful completion of the module, students should be able to: Fit, predict and understand time series models. Implement time series decompositions, exponential smoothing and ARIMA models.

Teaching & Learning methods

Assessment

	Autumn Supplementals/Resits
	Are supplemental/resit registrations permitted? No

	Pre-Requisites
	This module is for Registered Research students. Permission is required from the Head of the Mathematics and Statistics Department to take this module.

	Timetable
	This timetable is not currently available, please contact the Mathematics And Statistics Department.

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