[R-sig-eco] Behavioural data analysis using maximum likelihood in R
Oliver Hooker
oliverhooker at prstatistics.com
Mon Feb 19 18:12:02 CET 2018
This course may interest some studying animal behaviour with a reference
to ecology.
PS statistics has a course on "Behavioural data analysis using maximum
likelihood in R" - learn how to build custom models for your behavioural
data using maximum likelihood.
This course will be relevant to any studying the behaviour in animals
(or humans).
https://www.psstatistics.com/course/behavioural-data-analysis-using-maximum-likelihood-bdml01/
The course is delivered by Dr. Will Hoppitt and will take place in
Glasgow from the 19th - 23rd March 2018
Course Overview:
This 5-day course will involve a combination of lectures and practical
sessions. Students will learn to build and fit custom models for
analysing behavioural data using maximum likelihood techniques in R.
This flexible approach allows a researcher to a) use a statistical model
that directly represents their hypothesis, in cases where standard
models are not appropriate and b) better understand how standard
statistical models (e.g. GLMs) are fitted, many of which are fitted by
maximum likelihood. Students will learn how to deal with binary, count
and continuous data, including time-to-event data which is commonly
encountered in behavioural analysis.
After successfully completing this course students should be able to:
1) fit a multi-parameter maximum likelihood model in R
2) derive likelihood functions for binary, count and continuous data
3) deal with time-to-event data
4) build custom models to test specific behavioural hypotheses
5) conduct hypothesis tests and construct confidence intervals
6) use Akaike’s information criterion (AIC) and model averaging
7) understand how maximum likelihood relates to Bayesian techniques
Please email oliverhooker at psstatistics.com with any questions or visit
our website.
Feel free to share this anywhere you see fit and also check out our
sister sites.
www.PRstatistics.com (ecology and life sciences)
www.PRinformatics.com (bioinformatics and data science)
www.PSstatisitcs.com (behaviour and cognition)
--
Oliver Hooker PhD.
PR statistics
2017 publications -
Ecosystem size predicts eco-morphological variability in post-glacial
diversification. Ecology and Evolution. In press.
The physiological costs of prey switching reinforce foraging
specialization. Journal of animal ecology.
prstatistics.com
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