Estimating population abundance for replicated counts data is a computationally intensive problem. N-mixture models are used …

Functional data can come from many different areas of study. Some of the most common examples come from finance (for example stock …

Neural Networks are an immensely useful class of machine learning model, with countless applications. Today we are going to analyze a …

Rcpp is an R library allowing for easy integration of C++ code in your R workflow. It allows you to create optimized functions for when …

Bootstrapping is a statistical technique for analyzing the distributional properties of sample data (such as variability and bias). It …

optimizeAPA is an R package which allows for multi-parameter optimization. That means you can use it to find the maximum (or the …

Welcome to the world of manifold regression! In part 2 we will apply manifold regression to a case study involving fMRI brain imaging …

Welcome to the world of manifold regression! In part 1 we will introduce the basic concepts, overview the theory behind regression on …

Working on a likelihood function that relies on the Poisson distribution with large mean \(\lambda\), I ran into the problem of …

Summary Ever wanted to add \(\LaTeX\) to your R plots? Well now you can, with tikz, and it will allow you to use \(\LaTeX\) code within …

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