tidymodlr: An R6 Class to Perform Analysis on Long Tidy Data
Transforms long data into a matrix form to allow for ease of input into modelling packages for regression, principal components, imputation or machine learning. It does this by pivoting on user defined columns, generating a key-value table for variable names to ensure one-to-one mappings are preserved. It is particularly useful when the indicator names in the columns are long descriptive strings, for example "Energy imports, net (% of energy use)". High level analysis wrapper functions for correlation and principal components analysis are provided.
ggm: Graphical Markov Models with Mixed Graphs
Provides functions for defining mixed graphs containing three types of edges, directed, undirected and bi-directed, with possibly multiple edges. These graphs are useful because they capture fundamental independence structures in multivariate distributions and in the induced distributions after marginalization and conditioning. The package is especially concerned with Gaussian graphical models for (i) ML estimation for directed acyclic graphs, undirected and bi-directed graphs and ancestral graph models (ii) testing several conditional independencies (iii) checking global identification of DAG Gaussian models with one latent variable (iv) testing Markov equivalences and generating Markov equivalent graphs of specific types.
📦 elaborator
📝 A 'shiny' Application for Exploring Laboratory Data
🔗 https://cran.r-project.org/web/packages/elaborator/index.html
🤖#RStats
elaborator: A 'shiny' Application for Exploring Laboratory Data
A novel concept for generating knowledge and gaining insights into laboratory data. You will be able to efficiently and easily explore your laboratory data from different perspectives. Janitza, S., Majumder, M., Mendolia, F., Jeske, S., & Kulmann, H. (2021) <<a href="https://doi.org/10.1007%2Fs43441-021-00318-4" target="_top">doi:10.1007/s43441-021-00318-4</a>>.
tower: Easy Middle Ware Library for 'shiny'
The best way to implement middle ware for 'shiny' Applications. 'tower' is designed to make implementing behavior on top of 'shiny' easy with a layering model for incoming HTTP requests and server sessions. 'tower' is a very minimal package with little overhead, it is mainly meant for other package developers to implement new behavior.
📦 ggscidca
📝 Plotting Decision Curve Analysis with Coloured Bars
🔗 https://cran.r-project.org/web/packages/ggscidca/index.html
🤖#RStats
ggscidca: Plotting Decision Curve Analysis with Coloured Bars
Decision curve analysis is a method for evaluating and comparing prediction models that incorporates clinical consequences, requires only the data set on which the models are tested, and can be applied to models that have either continuous or dichotomous results. The 'ggscidca' package adds coloured bars of discriminant relevance to the traditional decision curve. Improved practicality and aesthetics. This method was described by Balachandran VP (2015) <<a href="https://doi.org/10.1016%2FS1470-2045%2814%2971116-7" target="_top">doi:10.1016/S1470-2045(14)71116-7</a>>.
legendry: Extended Legends and Axes for 'ggplot2'
A 'ggplot2' extension that focusses on expanding the plotter's arsenal of guides. Guides in 'ggplot2' include axes and legends. 'legendry' offers new axes and annotation options, as well as new legends and colour displays.
ggsector: Draw Sectors
Some useful functions that can use 'grid' and 'ggplot2' to plot sectors and interact with 'Seurat' to plot gene expression percentages. Also, there are some examples of how to draw sectors in 'ComplexHeatmap'.
📦 shinyfilter
📝 Use Interdependent Filters on Table Columns in Shiny Apps
🔗 https://cran.r-project.org/web/packages/shinyfilter/index.html
🤖#RStats
shinyfilter: Use Interdependent Filters on Table Columns in Shiny Apps
Allows to connect 'selectizeInputs' widgets as filters to a 'reactable' table. As known from spreadsheet applications, column filters are interdependent, so each filter only shows the values that are really available at the moment based on the current selection in other filters. Filter values currently not available (and also those being available) can be shown via popovers or tooltips.
📦 tidyCpp
📝 Tidy C++ Header-Only Definitions for Parts of the C API of R
🔗 https://cran.r-project.org/web/packages/tidyCpp/index.html
🤖#RStats
tidyCpp: Tidy C++ Header-Only Definitions for Parts of the C API of R
Core parts of the C API of R are wrapped in a C++ namespace via a set of inline functions giving a tidier representation of the underlying data structures and functionality using a header-only implementation without additional dependencies.
tidyrgee: 'tidyverse' Methods for 'Earth Engine'
Provides 'tidyverse' methods for wrangling and analyzing 'Earth Engine' <<a href="https://earthengine.google.com/" target="_top">https://earthengine.google.com/</a>> data. These methods help the user with filtering, joining and summarising 'Earth Engine' image collections.
