Statistics for dynamic modelling
This course starts with a lecture.
There is an assessed practical with this unit. If
you are enrolled on this course for credit it is your responsibility to
make sure that you have organised a group (of 3) with which to complete
this assessment. The assessment counts for 40% of the course mark.
Here is a list of background reading....
- An
Introduction to R Follow the Documentation links at CRAN for further
introductory material on R.
- For background on the theory of maximum likelihood estimation you
might like to look at pages 102-113 of Wood (2006) "Generalized Additive
Models:An Introduction with R", CRC Press, which covers all the theory we
will use, and gives further references.
- For a slower, and more detailed, look at likelihood based inference
from a practical perspective, take a look at
this
course on inference.
- The prerequisite for the course is
MA20226
or equivalent. The
notes
for the course are available online.
- If you don't have the prerequisites for the course and need to catch
up, you might want to try these introductory
statistics notes
- For the Bayesian MCMC material Section 15.8 of Press, Teukolsky,
Vetterling and Flannery (2007) "Numerical Recipes" (3rd Edition) is quite
a nice short introduction, while Gamermann's "Markov Chain Monte Carlo"
CRC (there are a couple of editions) is more detailed, but also very
clear.
- Chatfield "The analysis of timeseries" CRC (various editions)
provides an excellent introduction to its subject.
- Gurney and Nisbet (1998) "Ecological Dynamic modelling" Oxford, is a
very nice book on biological modelling aimed squarely at real systems.
- Britton (2003) "Essential Mathematical Biology" gives a good overview
of somewhat more abstract biological models.
- Turchin (2003) "Complex Population Dynamics", Princeton, is an
impressive example of how statistics and dynamic modelling can be
combined. One can argue with the technical approach, but the
basic philosophy is almost surely right.
Past papers...
Data...
- The
urchin data . These are digitized from figure 4.12 p107 of Gurney and
Nisbet (1998) Ecological Dynamics, Oxford. Units are 1000 mm^3 and years.
- The algae in chemostat data. Algal cell
counts versus hour.
- lbm.dat .
Notes...
Practicals (it's a really bad idea to look at the solutions before you
have got code to work for the labs, even if you struggle with them - the
struggling is part of the learning for this sort of work.) The solutions
are deliberately intended to be a bit cryptic if you have not attempted
the lab.