Rules of thumb for the design of ecological experiments Are you planning an experiment in the lab or field, or an observational study? Its a good idea to talk to a statistician before you start. Students often ask me for help with statistics after th... [Read more...]

Running R code for all combinations of some parameters with lapply karate Sometimes we want to run the same bit of code many times for different parameters. Then if we have multiple parameters, we may want to run the code for all combinations of those... [Read more...]

Current approaches to Species Distribution Modelling in R My course notes for “Current approaches to Species Distribution Modelling in R “ for World Fisheries Congress 2021 are now free online. The course covers tidyverse and sf workflows for models,... [Read more...]

Comparison of terra and stars packages The other day I wrote a comparison of raster and terra packages. The other newish raster package on the block is stars. So I go through the same code here. If you are starting out with stars, read their manual f... [Read more...]

A comparison of terra and raster packages The terra package looks designed to replace an old favourite raster. It is made by a similar team. The terra documentation states “can do more, is simpler to use, and it is faster.” So should you make the swi... [Read more...]

When interpolation doesn’t work with GAMs GAMs shouldn’t be used for extrapolation, and they can give strange results for interpolation too. Here I’ll explain why and we’ll look at a solution that involves changing the order a smoother’s penalty. Gaps... [Read more...]

How to solve common problems with GAMs Here I’ll provide solutions to some common problems I run into when fitting GAMs with mgcv and ways to solve them. The four problems are: Categorical variables should be input to gam() as factors ... [Read more...]

Fast functions with pipes Pipes are becoming popular R syntax, because they help make code more readable and can speed up coding. You can even use pipes to create functions. This is handy if you want to repeat a piped process for several different dat... [Read more...]

R workshops in Brisbane 2021 Our annual series of popular R workshops is on again between 5th and 12th February 2021, in person at the University of Queensland. Over the past 5 years we’ve successfully trained hundreds of academics, researchers and s... [Read more...]

New course on preparation and graphing of biological data in R We’re running a short online introduction to data preparation and graphing. The course will cover the basics of pre-processing data, including common data wrangling routines. We will use r... [Read more...]

Correcting for confounded variables with GLMs General (and generalized) linear models can be useful for analyzing field data, where sampling is often distributed unevenly across different environmental gradients or treatment groups. They help us corre... [Read more...]

Universal inference in R When we perform a statistical test we’d like to have confidence what the Type I error rate is what we say it is (rate of false positive findings). Often scientists choose a rate (AKA ‘alpha’) of 0.05 for rejecting the nu... [Read more...]

Time sinks for data wrangling Estimating the time it will take to complete a project is an important part of being a successful PhD student, researcher or consultant. A major time sink on many analytical projects is data wrangling. Often the wranglin... [Read more...]

How much has the data informed your isotope mixing model? The contributions of different food sources to animal diets is often a mystery. Isotopes provide a means to estimate those contributions, because different food sources often have different iso... [Read more...]

A case against pipes in R and what to do instead Pipes (%__%) are great for improving readibility of lengthy data processing scripts, but I’m beggining to learn they have some weaknesses when it comes to large and complex data processing. We are ... [Read more...]

Spatial predictions with GAMs and rasters One powerful use of GAMs is for interpolating to unsampled locations. We can combine GAMs with raster package to conveniently predict a GAM model to places we have not got data. Simulate some spatial data We... [Read more...]

Three ways to calculate distances in R Calculating a distance on a map sounds straightforward, but it can be confusing how many different ways there are to do this in R. This complexity arises because there are different ways of defining ‘distance?... [Read more...]

Using R and power analysis to inform experimental design A collaborator once asked me: “can you do that thing where you take a little bit of data and model it up to make lots more data?” Does it sound suspicious to fake a lot of data from a littl... [Read more...]

Make a map of your study site with tmap I’m loving the tmap package right now. Here’s why. And we’ll look at how to make a clean map of a study site as we go. We’ll use the data from our study of pollution and coral ... [Read more...]

Informing priors for a time-series models to detect declines in tiger sharks Our new research has revealed a 71% decline in tiger sharks across Queensland’s coastline (open-access version). In this blog I will explore the time-series modelling tech... [Read more...]