I have participated in a range of statistical, machine learning, and R development projects. I am a certified data analyst, data scientist and data product developer. I have paid much attention to data storage, curation, and quality control, as well as to the different approaches to software development, R code organization, packaging, and good practices during agile development.
From the analytical perspective, I dislike and abandoned p-values long ago. I tend to think in terms of null models and feasible sets (the possible range in pattern, without which no given pattern has any meaning). I have worked on complex problems involving clustering and ordination, variation partitioning, network analyses, structural equation modeling. I try to be as consistent and transparent as possible during the development of analytical projects, ensuring reproducibility and minimizing cherry-picking.
My last obsession is uncertainty and how to use general approaches to account for it through the many steps in the process of inference, from failure to collect the target individual tree, to misidentifications in herbarium, and down to confidence intervals in the parameters of fitted models or uncertainty about assumptions like independence of observations.
Below there is a gallery with examples of the figures we have created for scientific papers, presentations, etc. I hope it provides a good visual overview of the type of work I do.
From the analytical perspective, I dislike and abandoned p-values long ago. I tend to think in terms of null models and feasible sets (the possible range in pattern, without which no given pattern has any meaning). I have worked on complex problems involving clustering and ordination, variation partitioning, network analyses, structural equation modeling. I try to be as consistent and transparent as possible during the development of analytical projects, ensuring reproducibility and minimizing cherry-picking.
My last obsession is uncertainty and how to use general approaches to account for it through the many steps in the process of inference, from failure to collect the target individual tree, to misidentifications in herbarium, and down to confidence intervals in the parameters of fitted models or uncertainty about assumptions like independence of observations.
Below there is a gallery with examples of the figures we have created for scientific papers, presentations, etc. I hope it provides a good visual overview of the type of work I do.