Christoforos Anagnostopoulos

computational statistics, machine learning and streaming data analysis (download my cv or link in)

  • personal information and research interests
  • publications
  • invited talks
  • code (NEW)
  • teaching - Statistical Modelling II
  • teaching - Official Statistics
  • teaching - Graphical Modelling
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2011-2012. Statistical Modelling II (M3S2/M4S2/M5S2).

In this course, the linear model is generalized in several directions, and the resulting framework is investigated from a theoretical and practical perspective. The course is in three parts:
  • Part A: The Generalised Linear Model as a unifying statistical framework.
  • Part B: Random and mixed effects models.
  • Part C: Generalized Additive Models.
The R statistical package will be used to expose how the different models can be applied on example data.

Announcements

  • No lecture on Tuesday 15/01.

Course Materials

Datasets, R demos:

Schedule (please check weekly):

Assessment:

The course will be assessed as follows (CONFIRMED):

  • Coursework: 10%
  • 4 Exam Questions: 90% (3rd year) / 72% (4th year)
  • Mastery Project: 18% (4th year only)

Proposed Reading

  • An Introduction to Generalized Linear Models (2008). Third Edition, Annette J. Dobson, Adrian G. Barnett. Chapman & Hall/CRC
  • Statistical Modelling in R (2009), Murray Aitkin, Brian Francis, John Hinde and Ross Darnell, OUP
  • Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models, Julian Faraway, CRC press
  • Generalized Additive Models: An Introduction with R. Wood, S. N. (2006). Chapman & Hall/CRC.
  • R in a nutshell (2010). Joseph Adler, O’Reilly


canagnos [at] imperial [dot] ac [dot] uk