302376 (v.2) Advanced Statistical Inference 402
| Area: | Department of Mathematics and Statistics |
| Credits: | 25.0 |
| Contact Hours: | 3.0 |
| Lecture: | 3 x 1 Hours Weekly |
| Syllabus: | Basic principles and methods of inference for stochastic processes. Inference for special models - branching processes, discrete time Markov chains, continuous time marker chain. Large sample theory for the estimates. Statistical inference for point processes. |
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| Text and references listed above are for your information only and current as of September 30, 2003. Please check with the unit coordinator for up-to-date information. |
| Unit References: | Bassava, I.V. and Rao, L.S.P. Statistical Inference for Stachastic Processes Academic Press, 1980 ;Cox, D.R. and Hinkley, D.V. Theoretical Statistics Chapman & Hall, 1974 ;Aderson, P.K., Borgan, O., Gill R.D. and Keiding, N. Statistical Models Based onCounting Processes, Springer Verlag, 1993 ;Guttorp, P. Statistical Inference for Branching Processes, John Wiley & Sons, 1991 ;Lawless J.F. Statistical Models and Methods for Life-time Data, John Wiley & Sons; |
| Unit Texts: | No textbook required. |
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| Year | Location | Period | Internal | Area External | Central External | | 2004 | Bentley Campus | Semester 2 | Y | | | |
Current as of: February 2, 2004
CRICOS provider code 00301J
