Design single-case phase, alternation and multiple-baseline experiments, and conduct randomization tests on data gathered by means of such designs, as discussed in Bulte and Onghena (2013) <doi:10.22237/jmasm/1383280020>.

A package to make graphical representations of single case
data and to transform graphical displays back to raw data. The
package also includes tools for visually analyzing single-case
data, by displaying central location, variability and trend.

A package to make graphical representations of single case data and to transform graphical displays back to raw data. The package also includes tools for visually analyzing single-case data, by displaying central location, variability and trend.

Make graphical representations of single case data and transform graphical displays back to raw data. The package also includes tools for visually analyzing single-case data, by displaying central location, variability and trend.

Make graphical representations of single case data and transform graphical displays back to raw data, as discussed in Bulte and Onghena (2013) <doi:10.22237/jmasm/1383280020>. The package also includes tools for visually analyzing single-case data, by displaying central location, variability and trend.
ggExtra, ggplot2, graphics, plotly, scales, stats, utils

The package implements different inventory models, the
bullwhip effect and other supply chain performance variables.

Functions for Planning and Managing Inventories in a Supply
Chain
Implements different inventory models, the bullwhip effect and other supply chain performance variables. Marchena Marlene (2010) <arXiv:1009.3977>.

Generate Publication Ready Visualizations of Single Cell
Transcriptomics Data
person("Enrique", "Blanco-Carmona", email = "scpubr@gmail.com", role = c("cre", "aut"), comment = c(ORCID = "0000-0002-1208-1691"))
A system that provides a streamlined way of generating publication ready plots for known Single-Cell transcriptomics data in a “publication ready” format. This is, the aim is to automatically generate plots with the highest quality possible, that can be used right away or with minimal modifications for a research article.
rlang, Seurat, ggplot2, tidyr, dplyr, colorspace, viridis,
pbapply, patchwork, Nebulosa, ggbeeswarm, scales, stringr,
Matrix (>= 1.3.3), rmarkdown, knitr, purrr, testthat (>=
3.0.0), SeuratObject, qpdf, covr, circlize, ComplexHeatmap,
ggrepel, forcats, svglite, ggrastr, ggtext, pheatmap, ggExtra,
ggplotify, scattermore, ggdist, tibble, plyr, graphics,
magrittr, ggridges, ggsignif, infercnv, rjags, rgdal,
assertthat
Enrique Blanco-Carmona [cre, aut]
(<https://orcid.org/0000-0002-1208-1691>)