Time Series III

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Description

Time series consist of values of a variable recorded over a long period of time. Such data arise in just about every area of science and the humanities, including econometrics and finance, engineering, medicine, genetics, sociology, environmental science. What makes time series data special is the presence of dependence between observations in a series, and the fact that usually only one observation is made at any given point in time. This means that standard statistical methods are not appropriate, and special methods for statistical analysis are needed. This course provides an introduction to time series analysis using current methodology and software.

Objective

Content

Topics covered are: descriptive methods, plots, smoothing, differencing, the autocorrelation function, the correlogram and the variogram; the periodogram, estimation and elimination of trend and seasonal components; stationary processes, modelling and forecasting with autoregressive moving average (ARMA) models; spectral analysis, the fast Fourier transform, periodogram averages and other smooth estimates of the spectrum, time-invariant linear filters; non-stationary and seasonal time series models. ARIMA processes, identification, estimation and diagnostic checking, forecasting, including extrapolation of polynomial trends, exponential smoothing, and the Box-Jenkins approach.

Zudi Lu Lecturer for this course

Delivery

36 hours lectures, tutorials and practicals

Assessment

Ongoing assessment 30%, exam 70%.

Graduate attributes

• Applying mathematical knowledge (1)
• Interpreting data and drawing conclusions (2)
• Formulating mathematical problems (3)
• Problem solving skills (4)
• Flexibility in working environment (5)
• Communication skills (6)
• Team participation and leadership (7)
• Self-directed study (8)

Linkage past

Prerequisite is MATHS 1007A/B Mathematics I (Pass Div I) or MATHS 2004 Mathematics IIM (Pass Div I). One of STATS 1000 Statistical Practice I (Pass Div I) or STATS 2004 Laplace Transforms and Probability and Statistics (Pass), APP MTH 2009 Numerical Analysis and Probability and Statistics (Pass), STATS 2001 Statistical Methods (Civil) (pass).

Linkage present

No present linkages have been noted.

Linkage future

This course is not recorded as prequisite for other courses.

Restrictions

None.

Recommended text

None.