Target encoding is commonly used to map categorical variables to numeric with the objective of facilitating exploratory data analysis and machine learning modeling. This post covers the basics of this method, and explains how and when to use it.
R package for multicollinearity management in data frames with numeric and categorical variables.
In this post, I delve into the intricacies of model interpretation under the influence of multicollinearity, and use R and a toy data set to demonstrate how this phenomenon impacts both linear and machine learning models.
R package for spatial regression with Random Forest
R package to compare multivariate time-series.
R package to assess ecological memory in multivariate time-series.
R package to simulate pollen production of mono-specific tree populations over millennia.
We introduce distantia (v1.0.1), an R package providing general toolset to quantify dissimilarity between ecological time‐series, independently of their regularity and number of samples. The functions in distantia provide the means to compute dissimilarity scores by time and by shape and assess their significance, evaluate the partial contribution of each variable to dissimilarity, and align or combine sequences by similarity.
Paper published in the section "Editor's Choice" of the *Ecography* journal. It received [an award](https://www.dropbox.com/s/oacsy1xqx4omv1b/2019_BMB_Ecography_b_top_downloaded.png?dl=1) for the number of downloads during the 12 months after its publication.