University of Cambridge > Talks.cam > Statistics > Working with over-parameterized models

  Browse A-Z

Log in

Googledetails Microsoftdetails

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹī¸ Information

Working with over-parameterized models

Download to your calendar using vCal

If you have a question about this talk, please contact .

A parametric representation of a statistical model may involve some redundancy; that is, the mapping from parameter space to family of distributions may be many-to-one. Such over-parameterized representations are often very useful conceptually, but can cause computational and inferential problems (ridges in the likelihood, non-estimable parameter combinations). For linear and generalized-linear models, well known approaches use either a reduced basis or a generalized matrix inverse. In this talk I will discuss how to work with over-parameterized nonlinear models. Aspects covered will include maximum-likelihood computation, detection of non-identifiability, and presentation of results. Some implications for Bayesian analysis will also be touched upon. The work is motivated by the design and implementation of the R package “gnm” (written jointly with Dr Heather Turner).

This talk is part of the Statistics series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

One Whitehall Place, 2 Whitehall Court, London, SW1A 2EJ Economic orthodoxy and barriers to the low-carbon economy ai ethics

Other talks

Reproducibility In Astrophysical Simulations: The AGORA Initiative and a 14-Year Human Experiment (In Memory of Joel Primack) Sheref Mansy, topic TBA Cambridge RNA Club - ONLINE Loke CTR Annual Meeting 2026 - Epigenetics of embryogenesis and placentation Security Cooperation within Government and between Governments Science & the Public in Action: Can and should climate scientists be activists?
 

Š 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity