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 |
Prerequisite(s): |
5910 (v.4) Stochastic Processes 501 or any previous version
|
| |
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. |
| |
| ** 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 |
|
