BIOL 701 Likelihood Methods in Biology 2013

The course provides an introduction to likelihood-based inference in Biology. We will cover both theoretical and practical aspects of maximum likelihood and Bayesian inference.
Meeting: Monday and Wednesday 10:00-10:50AM in 2025 Haworth
The syllabus is available as a pdf by clicking here.
Instructors (office hours by appointment):
John 864-37065005 Haworth
Mark Holder 864-5789 6031 Haworth
Grades will be based on class participation and homework assignments. We will have approximately one homework assignment per week.


Date Topic and Links Assignments
Week 1 Jan 23 Probability, random variables, distributions
Week 2 Jan 28, Jan 30 Random samples, sample distributions, likelihood HW1_2013.doc
Week 3 Feb 04, Feb 06 Explicitly specifying variability: likelihood examples and Bayes' rule.
Notes on probability by Bálint Tóth
Week 4 Feb 11, Feb 13 Likelihood examples and maximum likelihood estimation
Week 5 Feb 18, Feb 20 Review / Likelihood ratio test statistic HW3_2013.doc (due Wed., Feb. 27)
Week 6 Feb 25, Feb 27 Generalized Linear Models Mark's notes on the lecture about testing with nuisance parameters
Week 7 Mar 04, Mar 06 Generalized Linear Models (continued) HW4_2013.doc (due March 13)
Week 8 Mar 11, Mar 13 Numerical Optimization/Parametric bootstrapping numerical_opt.pdf notes
num_opt_summary_example_code_intro.pdf Save this as and run using:
python 0.5 1000
You'll need Python and you'll need to install SciPy

Of you can check out the R version generalMismatchedFights.R.txt

which requires the data in a separate file: simpleData.txt

Mar 18 - Mar 22 SPRING BREAK
Week 9 Mar 25, Mar 27 Programming Intro, MCMCHomework5-2013.pdf (due Wed, April 3rd)
Notes: BayesianMCMC-2013.pdf
Week 10 Apr 01, Apr 03 MCMC continued
Week 11 Apr 08, Apr 10 Multiparameter MCMC latent_variable_MCMC.pdf (notes)
See for a Python template.
An R template is at coin_contamination.R it will write files called MCMC-output.txt and MCMC-samples.txt to its working directory.
Code snippet for running Gelman-Rubin diagnostic on tabular MCMC output.
Convergence Diagnostics Notes by Patrick K. Lam.
Week 12 Apr 15, Apr 17 Hastings ratio and model jumping hastingsRatio.pdf
Week 13 Apr 22, Apr 24 MTH's notes on JKK's lecture: source code and pdf The homework from 2011 that we discussed in class is here and this is a link to the GLM ML code that I discussed in class.
Week 14 Apr 29, May 01 Special topics: based on student suggestions Lewis et al paper with reversible jump move. Updated multi_parameter_mcmc.pdf notes.
First part of the last homework: Homework7-2013-preview.pdf
Homework7-2013.pdf (with corrections May 17th)
See (python) or (R) as your language preference dictates.
Week 15 May 06, May 08 Special topics: based on student suggestions