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Level: BSc, MSci, MSc
Title: Likelihood
Supervisor:

Dr Hugo Maruri-Aguilar
Research Area: Probability and Applications [Including Statistics]
Description:

Likelihood is commonly used as a technique for parameter estimation, closer to the frequentist data approach. In this project, through a series of problems we will explore and develop some ideas that show that likelihood is a multifaceted tool that can be used not only for inference but also for testing model fit. As part of this project, we will explore different ways of partitioning the likelihood information in the presence of nuisance parameters.
Further Reading:
  • D.A. Sprott and J.D. Kalbfleisch, Examples of likelihoods and comparison with point estimates and large sample approximations, JASA 64 326 (1969) 468–484.
  • D.A. Sprott, Statistical inference in science. Springer, New York, 2000.
Key Modules:

MTH5120 Statistical Modelling I (desirable)

MTH6136 Statistical Theory (desirable)
Other Information:

Desirable prerequisites for this project are regression (MTH5120 Statistical Modelling I, MTH6136 Statistical Theory) and either programming experience or willingness to acquire it. Report to be written in LaTeX.
Current Availability: Yes