Publications by Bluecology blog
What analysis programs drive conservation science?
What analysis programs drive conservation science? With the International Congress for Conservation Biology on at the end of July I was wondering, what analysis programs are supporting conservation science? And, what programs support spatial analysis and mapping? I ran a quick poll on my blog (you can take it here) to find out. Here are the resul...
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Impact of the conservation optimism hashtag
Impact of the conservation optimism hashtag The hashtag #conservationoptimism became popular during the recent International Congress for Conservation Biology symposium. Michael Burgass asked me what its twitter impact was, so here is a quick analysis. Michael also asked about #iamaconservationist, but that has too few tweets so far to make for ...
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seascapemodels.org version 2
seascapemodels.org version 2 I just (8-8-2017) updated my webpage to version 2 styling. If something is missing that you use, please let me know. Hope you enjoy the new page. Related To leave a comment for the author, please follow the link and comment on their blog: Bluecology blog. R-bloggers.com offers daily e-mail updates about R news and...
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Some thoughts about Bayesian Kriging in INLA
Some thoughts about Bayesian Kriging in INLA I have been playing around with spatial modelling in the R INLA package. This blog just records a few thoughts I have had about using INLA for kriging (spatial interpolation). I am keen to discuss these ideas with others. Kriging is super useful tool for ‘filling in the gaps’ between sampling sites...
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Stay motivated with R programming by knowing your emotions
Stay motivated with R programming by knowing your emotions We don’t usually think of programming as an ‘emotional’ experience. It is all code and computer logic and if using R, probably statistics. But recognising the emotions you face when programming can help you be more productive. In fact if you ask R about emotions it will probably tel...
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Checking residual distributions for non-normal GLMs
Checking residual distributions for non-normal GLMs Quantile-quantile plots If you are fitting a linear regression with Gaussian (normally distributed) errors, then one of the standard checks is to make sure the residuals are approximately normally distributed. It is a good idea to do these checks for non-normal GLMs too, to make sure your residu...
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General Linear Models The Basics
General Linear Models: The Basics General linear models are one of the most widely used statistical tool in the biological sciences. This may be because they are so flexible and they can address many different problems, that they provide useful outputs about statistical significance AND effect sizes, or just that they are easy to run in many comm...
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How do I calculate the R squared metric for a Bayesian model
How do I calculate the R squared metric for a Bayesian model? A good friend I met on a field trip long ago, Dominique Roche, recently emailed me to ask about evaluation of Bayesian models. He has been delving into generalized linear models, using Bayesian methods, and needed to decide what criteria he should use for model simplification (the proc...
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Should I learn sf or sp for spatial R programming
Should I learn sf or sp for spatial R programming? I recently received an email about some of the short-courses on my webpage. The correspondant was asked whether my course on Maps and GIS in R was still relevant, it being written in 2014. The R environment is changing so fast, it is worth asking whether course material that is a few years old is...
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How do I interpret the AIC
How do I interpret the AIC? My student asked today how to interpret the AIC (Akaike’s Information Criteria) statistic for model selection. We ended up bashing out some R code to demonstrate how to calculate the AIC for a simple GLM (general linear model). I always think if you can understand the derivation of a statistic, it is much easier to r...
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