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
Instructors (office hours by appointment):
|Ford Ballantyneemail@example.com||864-1868||154 Higuchi|
|John Kellyfirstname.lastname@example.org||864-3706||5005 Haworth|
|Mark Holderemail@example.com||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 24, Jan 26||Probability, random variables, distributions|
|Week 2 Jan 31, Feb 02||Random samples, sample distributions, likelihood|
|Week 3 Feb 07, Feb 09|| Explicitly specifying variability: likelihood examples and Bayes' rule.
Notes on probability by Bálint Tóth
|Assignment 1 (due Wed. Feb 16th)|
|Week 4 Feb 14, Feb 16||Likelihood examples and maximum likelihood estimation||Assignment 2 (due Wed. Feb 23rd).|
|Week 5 Feb 21, Feb 23||Review / Likelihoo ratio test statistic|
|Week 6 Feb 28, Mar 02|| Model Selection/Parametric bootstrapping
Some notes from lecture..
| Assignment 3.
The example to contemplate for Monday's class
|Week 7 Mar 07, Mar 09|| Computational aspects: numerical optimization.
Notes on sufficiency and identifiability
|Week 8 Mar 14, Mar 16|| Computational aspects: numerical optimization (continued)
generalMismatchedFights.R.txt - R script
generalMismatchedFights.py.txt - Python script
genericMultiParamLRTest.py.txt - a more general Python script
simpleData.txt - data set used by the R and "generic" Python script
|2011_LHM_HW4.txt the homework assignment.
templateParametricBoot.py.txt (probably the best python template for the homework).
|Mar 21 - Mar 27||SPRING BREAK|
|Week 9 Mar 28, Mar 30||Generalized Linear Models||
Homework 5 2011_LHM_HW5.pdf
Homework 5 Excel spreadsheat CAD_data.xls
Template for the homework: hw5templateParametricBoot.py.txt
|Week 10 Apr 04, Apr 06||Generalized Linear Models (continued)|
|Week 11 Apr 11, Apr 13||Generalized Linear Models (continued)|
|Week 12 Apr 18, Apr 20||more Generalized Linear Models||Homework 6 (due Wed. Apr 27th): HW6.doc Updated Apr. 21
Data file: skinks_eat_bugs.csv
Template: template_HW6.py.txt Updated Apr. 23
|Week 13 Apr 25, Apr 27|| Computational aspects of Bayesian inference: Markov chain Monte Carlo (MCMC).
Some notes: 2011_lhm_bayesian_mcmc_1.pdf
|Week 14 May 02, May 04|| Multiparameter MCMC. latent_variable_MCMC.pdf (notes)
Code for MCMC over the five parameters: gekko_glm_mcmc.py.txt
Code for MCMC over the five parameters and the latent variables: latent_gekko_svl.py.txt
Slides for Wed, May 4th lecture latentVarSlides.pdf
Peter Green posts a link to "Trans-dimensional Markov chain Monte Carlo" on his site: http://www.maths.bris.ac.uk/~mapjg/Papers.html
|Homework 7: 2011_LHM_HW7.pdf
the data: fertilization_data.csv
the (hopefully) easier template to use: 2011_LHM_HW7_template.py.txt
|Week 15 May 09, May 11|| Hastings ratio and model jumping
Some slides: hastingsRatio.pdf
More slides: bayesFactorLecture.pdf
|Homework 8: 2011_LHM_HW8.pdf|