Reproduce Statistical Analyses and Meta-Analyses (reproducer)
The reproducer R package includes data analysis functions and data sets (e.g., related to software defect prediction) to streamline reproducible research in software engineering.
Finding and plotting simple basis vectors for multivariate data (prinsimp)
Provides capabilities beyond principal components analysis to focus on finding structure in low variability subspaces. Constructs and plots simple basis vectors for pre-defined and user-defined measures of simplicity.
Mountain Plots, Folded Empirical Cumulative Distribution Plots (mountainplot)
Lattice functions for drawing folded empirical cumulative distribution plots, or mountain plots. A mountain plot is similar to an empirical CDF plot, except that the curve increases from 0 to 0.5, then decreases from 0.5 to 1 using an inverted scale at the right side. See: Monti (1995), Folded empirical distribution function curves-mountain plots. The American Statistician, 49, 342-345.
Methods that Apply to Rows and Columns of a Matrix (matrixStats)
Methods operating on rows and columns of matrices, e.g. col / rowMedians(), col / rowRanks(), and col / rowSds(). There are also some vector-based methods, e.g. binMeans(), madDiff() and weightedMedians(). All methods have been optimized for speed and memory usage.
Probabilistic Fisher Discriminant Analysis (probFDA)
Probabilistic Fisher discriminant analysis (pFDA) is a probabilistic version of the popular and powerful Fisher linear discriminant analysis for dimensionality reduction and classification.
Functions for Time Series Analysis (funtimes)
Includes non-parametric estimators and tests for time series analysis. The functions allow to test for presence of possibly non-monotonic trends and for synchronism of trends in multiple time series, using modern bootstrap techniques and robust non-parametric difference-based estimators.