TOC

  • stoichcalc: R Functions for Solving Stoichiometric Equations
  • inters: Flexible Tools for Estimating Interactions
  • MorphoTools2: Multivariate Morphometric Analysis
  • spiralize: Visualize Data on Spirals
  • autostats: Auto Stats
  • utile.tools: Summarize Data for Publication
  • ucie: Mapping 3D Data into CIELab Color Space
  • metaumbrella: Umbrella Review Package for R
  • diffcor: Fisher's z-Tests Concerning Difference of Correlations
  • figpatch: Easily Arrange External Figures with Patchwork Alongside 'ggplot2' Figures
  • esquisse: Explore and Visualize Your Data Interactively
  • muHVT: Constructing Hierarchical Voronoi Tessellations and Overlay Heatmap for Data Analysis

Introduction

Each month I will describe the package that I've discovered or rediscovered and the ones that I've used the most of my time. I will start with the package used in my work and the the one that I would like to try/did not had time to use for work and also fun

Each card is organised as this

Name of the package: short description

mytags: #example tag

links
[cran package link]
[cran vignette link]
[github link]

description from the author/vignette

mynotes

stoichcalc: R Functions for Solving Stoichiometric Equations

mytags: #chemistry #stoichiometry links
[cran package link] https://CRAN.R-project.org/package=stoichcalc
[vignette link]
[github link]

description from the author/vignette

Given a list of substance compositions, a list of substances involved in a process, and a list of constraints in addition to mass conservation of elementary constituents, the package contains functions to build the substance composition matrix, to analyze the uniqueness of process stoichiometry, and to calculate stoichiometric coefficients if process stoichiometry is unique. (See Reichert, P. and Schuwirth, N., A generic framework for deriving process stoichiometry in enviromental models, Environmental Modelling and Software 25, 1241-1251, 2010 for more details.)

mynotes

inters: Flexible Tools for Estimating Interactions

mytags: #statistics #interactions links
[cran package link] https://CRAN.R-project.org/package=inters
[vignette link] https://cran.r-project.org/web/packages/inters/vignettes/post-double-selection.html [github link] https://github.com/mattblackwell/inters/issues

description from the author/vignette

A set of functions to estimate interactions flexibly in the face of possibly many controls. Implements the procedures described in Blackwell and Olson (2022) doi:10.1093/restud/rdt044. mynotes

MorphoTools2: Multivariate Morphometric Analysis

mytags: #statistics #multivatiate links
[cran package link] https://CRAN.R-project.org/package=MorphoTools2
[vignette link] https://cran.r-project.org/web/packages/MorphoTools2/vignettes/MorphoTools2_tutorial.pdf
[github link] https://github.com/MarekSlenker/MorphoTools2/issues

description from the author/vignette

Tools for multivariate analyses of morphological data, wrapped in one package, to make the workflow convenient and fast. Statistical and graphical tools provide a comprehensive framework for checking and manipulating input data, statistical analyses, and visualization of results. Several methods are provided for the analysis of raw data, to make the dataset ready for downstream analyses. Integrated statistical methods include hierarchical classification, principal component analysis, principal coordinates analysis, non-metric multidimensional scaling, and multiple discriminant analyses:canonical, stepwise, and classificatory (linear, quadratic, and the non-parametric k nearest neighbours). The philosophy of the package will be described in Šlenker et al. (in prep). mynotes

spiralize: Visualize Data on Spirals

mytags: #statistic #visualization #plot links
[cran package link] https://CRAN.R-project.org/package=spiralize
[vignette link] https://cran.r-project.org/web/packages/spiralize/vignettes/spiralize.html
[github link] https://github.com/jokergoo/spiralize

description from the author/vignette

It visualizes data along an Archimedean spiral https://en.wikipedia.org/wiki/Archimedean_spiral, makes so-called spiral graph or spiral chart. It has two major advantages for visualization: 1. It is able to visualize data with very long axis with high resolution. 2. It is efficient for time series data to reveal periodic patterns.. mynotes

autostats: Auto Stats

mytags: #statistic #reports #exploration links
[cran package link] https://CRAN.R-project.org/package=autostats
[vignette link] https://cran.r-project.org/web/packages/autostats/vignettes/autostats.html
[github link] https://github.com/Harrison4192/

description from the author/vignette

Automatically do statistical exploration. Create formulas using 'tidyselect' syntax, and then determine cross-validated model accuracy and variable contributions using 'glm' and 'xgboost'. Contains additional helper functions to create and modify formulas. Has a flagship function to quickly determine relationships between categorical and continuous variables in the data set.

mynotes

utile.tools: Summarize Data for Publication

mytags: #statistic #reports #exploration links
[cran package link] https://CRAN.R-project.org/package=utile.tools
[github link] https://github.com/efinite/

description from the author/vignette

A set of tools for preparing and summarizing data for publication purposes. Includes functions for tabulating models, means to produce human-readable summary statistics from raw data, macros for calculating duration of time, and simplistic hypothesis testing tools.

mynotes

ucie: Mapping 3D Data into CIELab Color Space

mytags: #ciealab #Color Space links
[cran package link] https://CRAN.R-project.org/package=ucie

description from the author/vignette

Returns a data frame with the names of the input data points and hex colors (or CIELab coordinates). Data can be mapped to colors for use in data visualization. It optimally maps data points into a polygon that represents the CIELab colour space. Since Euclidean distance approximates relative perceptual differences in CIELab color space, the result is a color encoding that aims to capture much of the structure of the original data.

mynotes

metaumbrella: Umbrella Review Package for R

mytags: #statistics #umbrella links
[cran package link] https://CRAN.R-project.org/package=metaumbrella
[vignette link] https://cran.r-project.org/web/packages/metaumbrella/vignettes/forest_plot.html
https://cran.r-project.org/web/packages/metaumbrella/vignettes/stratification_evidence.html
https://cran.r-project.org/web/packages/metaumbrella/vignettes/train_well_formatted_dataset.html

description from the author/vignette

A comprehensive range of facilities to perform umbrella reviews with stratification of the evidence in R. The package accomplishes this aim by building on three core functions that:(i) automatically perform all required calculations in an umbrella review (including but not limited to meta-analyses), (ii) stratify evidence according to various classification criteria, and (iii) generate a visual representation of the results. Note that if you are not familiar with R, the core features of this package are available from a web browser (https://www.metaumbrella.org/). mynotes

diffcor: Fisher's z-Tests Concerning Difference of Correlations

mytags: #statistics #Fisher's links
[cran package link] https://CRAN.R-project.org/package=diffcor

description from the author/vignette

Computations of Fisher's z-tests concerning differences between correlations. diffcor.one() can be used to test whether an expected value differs from an observed value, for example, in construct validation. diffcor.two() can be used to test if the correlation between two constructs differed between two studies. diffcor.dep() can be applied to check if the correlation between two constructs (r12) is significantly different from the correlation of the first construct with a third one (r13), given the intercorrelation of the compared constructs (r23). All outputs provide the compared correlations, test statistic in z-units, and p-values. For diffcor.one() and diffcor.two(), the output further provides confidence intervals of the empirical correlations and the effect size Cohens q. According to Cohen (1988), q = |.10|, |.30| and |.50| are considered small, moderate, and large differences, respectively.

mynotes

figpatch: Easily Arrange External Figures with Patchwork Alongside 'ggplot2' Figures

mytags: #statistics #ggplot links
[cran package link] https://CRAN.R-project.org/package=figpatch

description from the author/vignette

For including external figures into an assembled {patchwork}. This enables the creation of more complex figures that include images alongside plots.

mynotes

esquisse: Explore and Visualize Your Data Interactively

mytags: #statistics #ggplot links
[cran package link] https://CRAN.R-project.org/package=esquisse
[vignette link] https://cran.r-project.org/web/packages/esquisse/vignettes/get-started.html
[github link] https://github.com/dreamRs/

description from the author/vignette

A 'shiny' gadget to create 'ggplot2' figures interactively with drag-and-drop to map your variables to different aesthetics. You can quickly visualize your data accordingly to their type, export in various formats, and retrieve the code to reproduce the plot.

mynotes

muHVT: Constructing Hierarchical Voronoi Tessellations and Overlay Heatmap for Data Analysis

mytags: #voronoi #plots links
[cran package link] https://CRAN.R-project.org/package=muHVT
[vignette link] https://cran.r-project.org/web/packages/muHVT/vignettes/muHVT.html
[github link] https://github.com/Mu-Sigma/muHVT/issues

description from the author/vignette

Constructing hierarchical voronoi tessellations for a given data set and overlay heatmap for variables at various levels of the tessellations for in-depth data analysis. See https://en.wikipedia.org/wiki/Voronoi_diagram for more information. Credits to Mu Sigma for their continuous support throughout the development of the package. mynotes