r-cran-estimability
GNU R package providing tools for determining estimability of linear functions
The estimability package is a GNU R package providing tools for
determining estimability of linear functions of regression coefficients,
and 'epredict' methods that handle non-estimable cases correctly.
r-cran-fontawesome
GNU R support of 'Font Awesome' Icons
Easily and flexibly insert 'Font Awesome' icons into 'R Markdown'
documents and 'Shiny' apps. These icons can be inserted into HTML content
through inline 'SVG' tags or 'i' tags. There is also a utility function for
exporting 'Font Awesome' icons as 'PNG' images for those situations where
raster graphics are needed.
python3-plaster
Python multi-format configuration file loader interface - Python 3.x module
plaster is a loader interface around arbitrary config file formats. It exists
to define a common API for applications to use when they wish to load
configuration settings.
mariadb-backup
Backup tool for MariaDB server
Based on Xtrabackup, but improved to work with MariaDB server.
This backup tool is guaranteed to be compatible with MariaDB server.
r-cran-paramhelpers
GNU R helpers for parameters in black-box optimization and tuning
Functions for parameter descriptions and operations in black-box
optimization, tuning and machine learning. Parameters can be described
(type, constraints, defaults, etc.), combined to parameter sets and can in
general be programmed on. A useful OptPath object (archive) to log function
evaluations is also provided.
r-cran-psych
GNU R procedures for psychological, psychometric, and personality research
This GNU R package provides a general purpose toolbox for personality,
psychometric theory and experimental psychology. Functions are primarily
for multivariate analysis and scale construction using factor
analysis, principal component analysis, cluster analysis and
reliability analysis, although others provide basic descriptive
statistics. Item Response Theory is done using factor analysis of
tetrachoric and polychoric correlations. Functions for analyzing
data at multiple levels include within and between group
statistics, including correlations and factor analysis. Functions
for simulating and testing particular item and test structures are
included. Several functions serve as a useful front end for
structural equation modeling. Graphical displays of path diagrams,
factor analysis and structural equation models are created using
basic graphics. Some of the functions are written to support a
book on psychometric theory as well as publications in personality
research.