JiscMail Logo
Email discussion lists for the UK Education and Research communities

Help for BENTHOS Archives


BENTHOS Archives

BENTHOS Archives


BENTHOS@JISCMAIL.AC.UK


View:

Message:

[

First

|

Previous

|

Next

|

Last

]

By Topic:

[

First

|

Previous

|

Next

|

Last

]

By Author:

[

First

|

Previous

|

Next

|

Last

]

Font:

Proportional Font

LISTSERV Archives

LISTSERV Archives

BENTHOS Home

BENTHOS Home

BENTHOS  September 2018

BENTHOS September 2018

Options

Subscribe or Unsubscribe

Subscribe or Unsubscribe

Log In

Log In

Get Password

Get Password

Subject:

Applied Bayesian modelling for ecologists and epidemiologists

From:

Oliver Hooker <[log in to unmask]>

Reply-To:

Oliver Hooker <[log in to unmask]>

Date:

Sat, 15 Sep 2018 00:11:59 +0100

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (179 lines)

Applied Bayesian modelling for ecologists and epidemiologists (ABME04)

https://www.prstatistics.com/course/applied-bayesian-modelling-for-ecologists-and-epidemiologists-abme04/

This course will be delivered by Prof. Matt Denwood in Glasgow city centre form the 15th - 19th October 2018.

Course Overview:
This application-driven course will provide a founding in the basic theory & practice of Bayesian statistics, with a focus on MCMC modeling for ecological & epidemiological problems. Starting from a refresher on probability & likelihood, the course will take students all the way to cutting-edge applications such as state-space population modelling & spatial point-process modelling. By the end of the week, you should have a basic understanding of how common MCMC samplers work and how to program them, and have practical experience with the BUGS language for common ecological and epidemiological models. The experience gained will be a sufficient foundation enabling you to understand current papers using Bayesian methods, carry out simple Bayesian analyses on your own data and springboard into more elaborate applications such as dynamical, spatial and hierarchical modelling.

Monday 15th – Classes from 09:30 to 17:30
Module 1: Revision of likelihoods using full likelihood profiles and an introduction to the theory of Bayesian statistics. Probability and likelihood. Conditional, joint and total probability, independence, Baye’s law. Probability distributions. Uniform, Bernoulli, Binomial, Poisson, Gamma, Beta and Normal distributions – their range, parameters and common uses of Likelihood and parameter estimation by maximum likelihood. Numerical likelihood profiles and maximum likelihood. Introduction to Bayesian statistics.
Relationship between prior, likelihood & posterior distributions. Summarising a posterior distribution; The philosophical differences between frequentist & Bayesian statistics, & the practical implications of these.
Applying Bayes’ theorem to discrete & continuous data for common data types given different priors. Building a posterior profile for a given dataset, & compare the effect of different priors for the same data.

Tuesday 16th – Classes from 09:30 to 17:30
Module 2: An introduction to the workings of MCMC, and the potential dangers of MCMC inference.  Participants will program their own (basic) MCMC sampler to illustrate the concepts and fully understand the strengths and weaknesses of the general approach.  The day will end with an introduction to the bugs language.
Introduction to MCMC. The curse of dimensionality & the advantages of MCMC sampling to determine a posterior distribution. Monte Carlo integration, standard error, & summarising samples from posterior distributions in R. Writing a Metropolis algorithm & generating a posterior distribution for a simple problem using MCMC.
Markov chains, autocorrelation & convergence. Definition of a Markov chain. Autocorrelation, effective sample size and Monte Carlo error. The concept of a stationary distribution and burnin. Requirement for convergence diagnostics, and common statistics for assessing convergence. Adapting an existing Metropolis algorithm to use two chains, & assessing the effect of the sampling distribution on the autocorrelation. Introduction to BUGS & running simple models in JAGS. Introduction to the BUGS language & how a BUGS model is translated to an MCMC sampler during compilation. The difference between deterministic & stochastic nodes, & the contribution of priors & the likelihood. Running, extending & interpreting the output of simple JAGS models from within R using the runjags interface.

Wednesday 17th – Classes from 09:30 to 17:30
Module 3: Common models for which jags/bugs would be used in practice, with examples given for different types of model code.  All aspects of writing, running, assessing and interpreting these models will be extensively discussed so that participants are able and confident to run similar models on their own. There will be a particularly heavy focus on practical sessions during this day.  The day will finish with a discussion of how to assess the fit of mcmc models using the deviance information criterion (dic) and other methods. Using JAGS for common problems in biology. Understanding and generating code for basic generalised linear mixed models in JAGS. Syntax for quadratic terms and interaction terms in JAGS.
Essential fitting tips and model selection. The need for minimal cross-correlation and independence between parameters and how to design a model with these properties. The practical methods and implications of minimizing Monte Carlo error and autocorrelation, including thinning. Interpreting the DIC for nested models, and understanding the limitations of how this is calculated. Other methods of model selection and where these might be more useful than DIC. Most commonly used methods Rationale and use for fixed threshold, ABGD, K/theta, PTP, GMYC with computer practicals. Other methods, Haplowebs, bGMYC, etc. with computer practicals.

Thursday 18th – Classes from 09:30 to 17:30
Module 4: The flexibility of MCMC, and precautions required for using MCMC to model commonly encountered datasets. An introduction to conjugate priors and the potential benefits of exploiting gibbs sampling will be given. More complex types of models such as hierarchical models, latent class models, mixture models and state space models will be introduced and discussed. The practical sessions will follow on from day 3.
General guidance for model specification. The flexibility of the BUGS language and MCMC methods. The difference between informative and diffuse priors. Conjugate priors and how they can be used. Gibbs sampling. State space models. Hierarchical and state space models. Latent class and mixture models. Conceptual application to animal movement. Hands-on application to population biology. Conceptual application to epidemiology.

Friday 19th – Classes from 09:30 to 17:30
Module 5: Additional practical guidance for the use of Bayesian methods in practice, and finish with a brief overview of more advanced Bayesian tools such as Integrated Nested Laplace Approximation (INLA) and stan.
Additional Bayesian methods. Understand the usefulness of conjugate priors for robust analysis of proportions (Binomial and Multinomial data). Be aware of some methods of prior elicitation. Advanced Bayesian tools. Strengths and weaknesses of INLA compared to BUGS. Strengths and weaknesses of stan compared to BUGS.

Email [log in to unmask]

Check out our sister sites,
www.PRstatistics.com (Ecology and Life Sciences)
www.PRinformatics.com (Bioinformatics and data science)
www.PSstatsistics.com (Behaviour and cognition)

1.    October 1st – 5th
TIME SERIES MODELS FOR ECOLOGISTS (TSME02)
Glasgow, Dr Andrew Parnell
https://www.prstatistics.com/course/time-series-models-foe-ecologists-tsme02/

2.    October 1st – 5th 2018
INTRODUCTION TO LINUX WORKFLOWS FOR BIOLOGISTS (IBUL03)
Glasgow, Scotland, Dr. Martin Jones
https://www.prinformatics.com/course/introduction-to-linux-workflows-for-biologists-ibul03/

3.    October 8th – 12th 2018
INTRODUCTION TO FREQUENTIST AND BAYESIAN MIXED (HIERARCHICAL) MODELS (IFBM01)
Glasgow, Scotland, Dr Andrew Parnell
https://www.psstatistics.com/course/introduction-to-frequentis-and-bayesian-mixed-models-ifbm01/

4.    October 15th – 19th 2018
APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS (ABME04)
Glasgow, Scotland, Dr. Matt Denwood, Emma Howard
http://www.prstatistics.com/course/applied-bayesian-modelling-ecologists-epidemiologists-abme04/

5.    October 23rd – 25th 2018
INTRODUCTIUON TO R (This is a private ‘in-house’ course)
London, England, Dr William Hoppitt

6.    October 29th – November 2nd 2018
INTRODCUTION TO R AND STATISTICS FOR BIOLOGISTS (IRFB02)
Glasgow, Scotland, Dr. Olivier Gauthier
https://www.prstatistics.com/course/introduction-to-statistics-and-r-for-biologists-irfb02/

7.    October 29th – November 2nd 2018
INTRODUCTION TO BIOINFORMATICS FOR DNA AND RNA SEQUENCE ANALYSIS (IBDR01)
Glasgow, Scotland, Dr Malachi Griffith, Dr. Obi Griffith
www.prinformatics.com/course/precision-medicine-bioinformatics-from-raw-genome-and-transcriptome-data-to-clinical-interpretation-pmbi01/

8.    November 5th – 8th  2018
PHYLOGENETIC COMPARATIVE METHODS FOR STUDYING DIVERSIFICATION AND PHENOTYPIC EVOLUTION (PCME01)
Glasgow, Scotland, Dr. Antigoni Kaliontzopoulou
https://www.prstatistics.com/course/phylogenetic-comparative-methods-for-studying-diversification-and-phenotypic-evolution-pcme01/

9.    November 19th – 23rd  2018
STRUCTUAL EQUATION MODELLING FOR ECOLOGISTS AND EVOLUTIONARY BIOLOGISTS (SEMR02)
Glasgow, Scotland, Dr. Jonathan Lefcheck
https://www.prstatistics.com/course/structural-equation-modelling-for-ecologists-and-evolutionary-biologists-semr02/

10.    November 26th – 30th 2018
FUNCTIONAL ECOLOGY FROM ORGANISM TO ECOSYSTEM: THEORY AND COMPUTATION (FEER01)
Glasgow, Scotland, Dr. Francesco de Bello, Dr. Lars Götzenberger, Dr. Carlos Carmona
http://www.prstatistics.com/course/functional-ecology-from-organism-to-ecosystem-theory-and-computation-feer01/

11.    December 3rd – 7th 2018
INTRODUCTION TO BAYESIAN DATA ANALYSIS FOR SOCIAL AND BEHAVIOURAL SCIENCES USING R AND STAN (BDRS01)
Glasgow, Dr. Mark Andrews
https://www.psstatistics.com/course/introduction-to-bayesian-data-analysis-for-social-and-behavioural-sciences-using-r-and-stan-bdrs01/

12.    January 21st – 25th 2019
STATISTICAL MODELLING OF TIME-TO-EVENT DATA USING SURVIVAL ANALYSIS: AN INTRODUCTION FOR ANIMAL BEHAVIOURISTS, ECOLOGISTS AND EVOLUTIONARY BIOLOGISTS (TTED01)
Glasgow, Scotland, Dr. Will Hoppitt
https://www.psstatistics.com/course/statistical-modelling-of-time-to-event-data-using-survival-analysis-tted01/

13.    January 21st – 25th 2019
ADVANCING IN STATISTICAL MODELLING USING R (ADVR08)
Glasgow, Scotland, Dr. Luc Bussiere, Dr. Tom Houslay
http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr08/

14.    January 28th–  February 1st 2019
AQUATIC ACOUSTIC TELEMETRY DATA ANALYSIS AND SURVEY DESIGN
Glasgow, Scotland, VEMCO staff and affiliates
https://www.prstatistics.com/course/aquatic-acoustic-telemetry-data-analysis-atda01/

15.    4th – 8th February 2019
DESIGNING RELIABLE AND EFFICIENT EXPERIMENTS FOR SOCIAL SCIENCES (DRES01)
Glasgow, Scotland, Dr. Daniel Lakens
https://www.psstatistics.com/course/designing-reliable-and-effecient-experiments-for-social-sciences-dres01/

16.    February 11th – 15th 2019
REPRODUCIBLE DATA SCIEDNCE FOR POPULATION GENETICS
Glasgow, Scotland, Dr. Thibaut Jombart, Dr. Zhain Kamvar
https://www.prstatistics.com/course/reproducible-data-science-for-population-genetics-rdpg02/

17.    25th February – 1st March 2019
MOVEMENT ECOLOGY (MOVE02)
Margam Discovery Centre, Wales, Dr. Luca Borger, Prof. Ronny Wilson, Dr Jonathan Potts
https://www.prstatistics.com/course/movement-ecology-move02/

18.    March 4th – 8th 2019
BIOACUSTIC DATA ANALYSIS
Glasgow, Scotland, Dr. Paul Howden-Leach
https://www.prstatistics.com/course/bioacoustics-for-ecologists-hardware-survey-design-and-data-analysis-biac01/

19.    March 11th – 15th  2019
ECOLOGICAL NICHE MODELLING USING R (ENMR03)
Glasgow, Scotland, Dr. Neftali Sillero
http://www.prstatistics.com/course/ecological-niche-modelling-using-r-enmr03/

20.    MARCH 18th – 22nd 2019
INTRODUCTION TO STATISTICS AND R FOR EVERYONE (IRFE01)
Crete, Greece, Dr Aristides (Aris) Moustakas
https://www.prstatistics.com/course/introduction-to-statistics-and-r-for-anyone-irfe01/

21.    March 25th – 29th 2019
LANDSCAPE GENETIC/GENOMIC DATA ANALYSIS USING R (LNDG03)
Glasgow, Scotland, Prof. Rodney Dyer
http://www.prstatistics.com/course/landscape-genetic-data-analysis-using-r-lndg03/

22.    A pril 1st – 5th 2019
INTRODUCTION TO STATISTICAL MODELLING FOR PSYCHOLOGISTS USING R (IPSY01)
Glasgow, Scotland, Dr. Dale Barr, Dr Luc Bussierre
http://www.psstatistics.com/course/introduction-to-statistics-using-r-for-psychologists-ipsy02/

23.    April 8th – 12th
MACHINE LEARNING
Glasgow Scotland, Dr Aristides (Aris) Moustakas
https://www.prstatistics.com/course/machine-learning-using-r-mlur01/


-- 
Oliver Hooker PhD.
PR statistics

2018 publications -

Alternative routes to piscivory: Contrasting growth trajectories in brown trout (Salmo trutta) ecotypes exhibiting contrasting life history strategies. Ecology of Freshwater Fish. DOI to follow

Phenotypic and resource use partitioning amongst sympatric lacustrine brown trout, Salmo trutta. Biological Journal of the Linnean Society. DOI 10.1093/biolinnean/bly032

prstatistics.com
facebook.com/prstatistics/
twitter.com/PRstatistics
groups.google.com/d/forum/pr-statistics-post-course-forum
prstatistics.com/organiser/oliver-hooker/

6 Hope Park Crescent
Edinburgh
EH8 9NA

+44 (0) 7966500340

########################################################################

To unsubscribe from the BENTHOS list, click the following link:
https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=BENTHOS&A=1

Top of Message | Previous Page | Permalink

JiscMail Tools


RSS Feeds and Sharing


Advanced Options


Archives

January 2019
December 2018
November 2018
October 2018
September 2018
August 2018
July 2018
June 2018
May 2018
April 2018
March 2018
February 2018
January 2018
November 2017
October 2017
September 2017
August 2017
July 2017
June 2017
May 2017
April 2017
March 2017
February 2017
January 2017
December 2016
November 2016
October 2016
September 2016
August 2016
July 2016
June 2016
May 2016
April 2016
March 2016
February 2016
January 2016
December 2015
November 2015
October 2015
September 2015
August 2015
July 2015
June 2015
May 2015
April 2015
March 2015
February 2015
January 2015
December 2014
November 2014
October 2014
September 2014
August 2014
July 2014
May 2014
April 2014
March 2014
February 2014
January 2014
December 2013
October 2013
September 2013
August 2013
July 2013
June 2013
May 2013
April 2013
March 2013
October 2012
November 2011
September 2011
May 2011
April 2011
March 2011
February 2011
January 2011
November 2010
July 2010
June 2010
May 2010
April 2010
February 2010
January 2010
November 2009
September 2009
July 2009
March 2009
November 2008
October 2008
September 2008
April 2008
March 2008
October 2007
August 2007
July 2007
June 2007
May 2007
February 2007
2006
2005
2004
2003
2002
2001
2000
1999


JiscMail is a Jisc service.

View our service policies at https://www.jiscmail.ac.uk/policyandsecurity/ and Jisc's privacy policy at https://www.jisc.ac.uk/website/privacy-notice

Secured by F-Secure Anti-Virus CataList Email List Search Powered by the LISTSERV Email List Manager