Statistical Consulting, Quantitative Ecology & More!

Ballina, NSW, Australia
Joined October 2022
And we're live! 🎉 Quantecol was started to provide statistical consulting services, ranging from experimental design advice and assisting graduate students to long-term collaborations on research projects. Keep us in mind for your statistical needs! 🙏
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New blog post! We show how to marginalise discrete variables from Bayesian ecological models in Stan and how to recover their posterior distributions after estimation. I cover occupancy and N-mixture models using multiple parameterisations and model types. quantecol.com.au/blog/margin…
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🔖New blog post! We wrote a post on why defaulting to Gaussian processes for spatial or temporal effects often makes more sense than traditional random effects. We use data on tadpoles and use @mcmc_stan to illustrate the straightforward implementation. quantecol.com.au/blog/gaussi…
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🚨 We launched a blog! In our first post, we explore how ecological models can be formulated as hidden Markov models and present a scalable formulation of the forward algorithm for increasingly complex models using Hamiltonian Monte Carlo in @mcmc_stan. quantecol.com.au/blog/hmm-in…
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Today we are #thankful for running a new parameterisation of a Jolly-Seber model without error messages on the first try in @R_nimble!
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This is the @R_nimble model code we're using to analyse our largest dataset yet. Can you see what we're doing? Bonus points to anyone that points out errors before we send this off for a month of MCMC. 🙏
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Robust design FTW! If disease sampling sensitivity (and/or specificity) is low, estimates for infection dynamics are incredibly biased in traditional multistate models.
Quantecol's first project! This was a great collaboration with researchers at @SCUonline, where Quantecol conducted dose-response analyses to investigate the effect of DMSO on biofilm formation.
New paper! Really great to work with this team and do some fun dose-response modeling. sciencedirect.com/science/ar…
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