Prequential Statistics
- đ¤ Speaker: Philip Dawid, Statistical Laboratory, Cambridge
- đ Date & Time: Thursday 01 November 2007, 16:00 - 18:00
- đ Venue: LR4, Engineering, Department of
Abstract
Prequential is a portmanteau word for predictive sequential—a broad statistical methodology founded on a view of data (like Mark Twain’s view of history) as “just one darned thing after another”. A variety of statistical methods might be applied to learn projectible regularities in a data-sequence so as to improve forecasting; prequential analysis assesses how well this has been done by contrasting one-step ahead forecasts with realised outcomes.
Many fundamental statistical concepts, such as consistency or efficiency, as well as techniques such as model selection, can be fruitfully redefined within this framework. This talk will outline the basic theory and some of its properties and applications.
Series This talk is part of the Machine Learning @ CUED series.
Included in Lists
- All Talks (aka the CURE list)
- Biology
- bld31
- Cambridge Centre for Data-Driven Discovery (C2D3)
- Cambridge Forum of Science and Humanities
- Cambridge Language Sciences
- Cambridge Neuroscience Seminars
- Cambridge talks
- CBL important
- Chris Davis' list
- Creating transparent intact animal organs for high-resolution 3D deep-tissue imaging
- dh539
- dh539
- Featured lists
- Guy Emerson's list
- Hanchen DaDaDash
- Inference Group Summary
- Information Engineering Division seminar list
- Interested Talks
- Joint Machine Learning Seminars
- Life Science
- Life Sciences
- LR4, Engineering, Department of
- Machine Learning @ CUED
- Machine Learning Summary
- ML
- ndk22's list
- Neuroscience
- Neuroscience Seminars
- Neuroscience Seminars
- ob366-ai4er
- Required lists for MLG
- rp587
- Seminar
- Simon Baker's List
- Stem Cells & Regenerative Medicine
- Trust & Technology Initiative - interesting events
- yk373's list
- yk449
Note: Ex-directory lists are not shown.
![[Talks.cam]](/static/images/talkslogosmall.gif)


Thursday 01 November 2007, 16:00-18:00