useR2026-dep.md

geocomputation with R:

install.packages(c("sf", "terra", "tmap", "spData",
                   "dplyr", "leaflet", "mapview"))

You can also use a docker image with everything already setup.

More here: https://github.com/geocompx/user26

Convex Optimization in R Using CVXR

Site web: https://bnaras.github.io/cvxr_tutorial/

An installation script is provided but this is what seems to be needed:

# Solvers (CVXR auto-pulls clarabel, osqp, scs, highs)
install.packages(c("CVXR", "scip", "Uno", "sparsediff"))

# Helpers used by the examples
install.packages(c("ggplot2", "RColorBrewer", "tidyr", "nnls",
                   "glmnet", "png", "bench"))

From Collecting Log-data to Analyzing Process Indicators with logLime R Package

From the zip file:

requiredCRANpackages <- sapply(c("dplyr", "tidyr", "pak", "arrow", "vroom",
                                 "ggplot2", "ggdensity", "gifski", "gganimate"),
                               require, character.only = TRUE, quietly = TRUE,
                               warn.conflicts = FALSE)
install.packages(names(requiredCRANpackages)[!requiredCRANpackages])

ip <- installed.packages()
if ("logLime" %in% rownames(ip)) {
  if (compareVersion(ip["logLime", "Version"], "0.3.4") < 0) {
    pak::pkg_install("tzoltak/logLime")
  }
}
if (!require(logLime, quietly = TRUE)) pak::pkg_install("tzoltak/logLime")

Introduction to spatial data science

GH repo: https://github.com/kadyb/user2026

install.packages(c("terra", "ggplot2", "tidyterra", "ggspatial"))

Modelling spatial density of geo-located point data

Not found