Variance Component Analysis (VCA)
ANOVA-type estimation (prediction) of random effects and variance components in linear mixed models, is implemented. Random models, a sub-set of mixed models, can be fit applying a Variance Component Analysis (VCA). This is a special type of analysis frequently used in verifying the precision performance of diagnostics. The Satterthwaite approximation of the total degrees of freedom is implemented. There are several functions for extracting, random effects, fixed effects, variance-covariance matrices of random and fixed effects. Residuals can be extracted as raw, standardized and studentized residuals. Additionally, a variability chart is implemented for visualizing the variability in sub-classes emerging from an experimental design (‘varPlot’).
Receiver Operating Characteristics Surface (ROCS)
Plots the Receiver Operating Characteristics Surface for high-throughput class-skewed data, calculates the Volume under the Surface (VUS) and the FDR-Controlled Area Under the Curve (FCAUC), and conducts tests to compare two ROC surfaces.
Integrated Code Chunk Anchoring and Referencing for R Markdown Documents (kfigr)
A streamlined cross-referencing system for R Markdown documents generated with ‘knitr’. R Markdown is an authoring format for generating dynamic content from R. ‘kfigr’ provides a hook for anchoring code chunks and a function to cross-reference document elements generated from said chunks, e.g. figures and tables.