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3 places left - Model-Based Multivariate Analysis of Abundance (presence/abscence) Data Using R - David Warton - England

Oliver Hooker
'Model base multivariate analysis of abundance (presence/absence) data
using R'

3 Places left!

Delivered by Prof. David Warton, Melbourne University

http://www.prstatistics.com/course/model-base-multivariate-analysis-of-abundance-data-using-r-mbmv01/

This course will run from 16th – 20th January 2017 at Juniper Hall
Field Station, Dorking, Surrey, just south of London, England.

OVERVIEW
This course will provide an introduction to modern multivariate
techniques, with a special focus on the analysis of abundance or
presence/absence data. Multivariate analysis in ecology has been
changing rapidly in recent years, with a focus now on formulating a
statistical model to capture key properties of the observed data, rather
than transformation of data using a dissimilarity-based framework.

In recent years, model-based techniques have been developed for
hypothesis testing, identifying indicator species, ordination,
clustering, predictive modelling, and use of species traits as
predictors to explain interspecific variation in environmental response.
These techniques are more interpretable than alternatives, have better
statistical properties, and can be used to address new problems, such as
the prediction of a species’ spatial distribution from its traits
alone.

INTENDED AUDIENCE
PhD students, research postgraduates, and practicing academics as well
as persons in industry working with multivariate data, especially when
recorded as presence/absences or some measure of abundance (counts,
biomass, % cover, etc).

Course content is as follows

Day 1: Revision of (univariate) regression analysis
o Revision of key “Stat 101” messages, the linear model, generalised
linear model and linear mixed model.
o Main packages: lme4.

Day 2: Computer-intensive inference and multiple responses
o The parametric bootstrap, permutation tests and the bootstrap, model
selection, classical multivariate analysis, allometric line fitting.
o Main packages: lme4, mvabund, glmnet, smatr.

Day 3: Multivariate abundance data
o Key properties, hypothesis testing, indicator species, compositional
analysis, non-standard models.
o Main packages: mvabund.

Day 4: Explaining cross-species patterns
o Classifying species based on environmental response, species traits as
predictors, studying species interactions.
o Main packages: Speciesmix, mvabund, lme4.

Day 5: Model-based ordination and inference
o Latent variable models for ordination, model-based inference for
fourth corner models.
o Main packages: boral, mvabund.

Please email any inquiries to [hidden email] or visit our
website www.prstatistics.com

Please feel free to distribute this material anywhere you feel is
suitable

Upcoming courses - email for details [hidden email]

1. MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R (January
2017) #MBMV
http://www.prstatistics.com/course/model-base-multivariate-analysis-of-abundance-data-using-r-mbmv01/

2. ADVANCED PYTHON FOR BIOLOGISTS (February 2017) #APYB
http://www.prstatistics.com/course/advanced-python-biologists-apyb01/

3. STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R
(February 2017) #SIMM
http://www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm03/

4. NETWORK ANAYLSIS FOR ECOLOGISTS USING R (March 2017) #NTWA
http://www.prstatistics.com/course/network-analysis-ecologists-ntwa01/

5. ADVANCES IN MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (April
2017) #MVSP
http://www.prstatistics.com/course/advances-in-spatial-analysis-of-multivariate-ecological-data-theory-and-practice-mvsp02/

6. INTRODUCTION TO STATISTICS AND R FOR BIOLOGISTS (April 2017) #IRFB
http://www.prstatistics.com/course/introduction-to-statistics-and-r-for-biologists-irfb02/

7. ADVANCING IN STATISTICAL MODELLING USING R (April 2017) #ADVR
http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr05/

8. INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (May 2017) #IBHM
http://www.prstatistics.com/course/introduction-to-bayesian-hierarchical-modelling-using-r-ibhm02/

9. GEOMETRIC MORPHOMETRICS USING R (June 2017) #GMMR
http://www.prstatistics.com/course/geometric-morphometrics-using-r-gmmr01/

10. MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (June 2017) #MASE
http://www.prstatistics.com/course/multivariate-analysis-of-spatial-ecological-data-using-r-mase01/

11. TIME SERIES MODELS FOR ECOLOGISTS USING R (JUNE 2017 (#TSME)

12. BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS (July 2017) #BIGB
http://www.prstatistics.com/course/bioinformatics-for-geneticists-and-biologists-bigb02/

13. SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (August 2017) #SPAE
http://www.prstatistics.com/course/spatial-analysis-ecological-data-using-r-spae05/

14. ECOLOGICAL NICHE MODELLING (October 2017) #ENMR
http://www.prstatistics.com/course/ecological-niche-modelling-using-r-enmr01/

15. INTRODUCTION TO BIOINFORMATICS USING LINUX (October 2017) #IBUL

16. APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS
(November 2017) #ABME
http://www.prstatistics.com/course/applied-bayesian-modelling-ecologists-epidemiologists-abme03/

17. INTRODUCTION TO METHODS FOR REMOTE SENSING (November 2017) #IRMS

18. INTRODUCTION TO PYTHON FOR BIOLOGISTS (November 2017) #IPYB

19. DATA VISUALISATION AND MANIPULATION USING PYTHON (December 2017)
#DVMP

20. ADVANCING IN STATISTICAL MODELLING USING R (December 2017) #ADVR

21. GENETIC DATA ANALYSIS USING R (October TBC)
22. LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (November TBC)
23. PHYLOGENETIC DATA ANALYSIS USING R (November TBC)
24. STRUCTURAL EQUATION MODELLING FOR ECOLOGISTS AND EVOLUTIONARY
BIOLOGISTS (TBC)

--
Oliver Hooker PhD.
PR statistics

3/1
128 Brunswick Street
Glasgow
G1 1TF

+44 (0) 7966500340

www.prstatistics.com
www.prstatistics.com/organiser/oliver-hooker/

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