This package provides Rcpp bindings for PLANC, a highly parallel and extensible NMF/NTF (Non-negative Matrix/Tensor Factorization) library.

This is software accompanying the book 'Applied Smoothing Techniques for Data Analysis---The Kernel Approach with S-Plus Illustrations', Oxford University Press. It provides smoothing methods for nonparametric regression and density estimation

The r-mhsmm package implements estimation and prediction methods for hidden Markov and semi-Markov models for multiple observation sequences. Such techniques are of interest when observed data is thought to be dependent on some unobserved (or hidden) state. Also, this package is suitable for equidistant time series data, with multivariate and/or missing data. Allows user defined emission distributions.

In this package Cardoso's JADE algorithm as well as his functions for joint diagonalization are ported to R. Also several other blind source separation (BSS) methods, like AMUSE and SOBI, and some criteria for performance evaluation of BSS algorithms, are given. The package is described in Miettinen, Nordhausen and Taskinen (2017) <doi:10.18637/jss.v076.i02>.

The biglm package lets you create a linear model object that uses only codep^2 memory for p variables. It can be updated with more data using update. This allows linear regression on data sets larger than memory.

This package contains linear and nonlinear regression methods based on partial least squares and penalization techniques. Model parameters are selected via cross-validation, and confidence intervals ans tests for the regression coefficients can be conducted via jackknifing.

This package lets you create a reproducible ggplot2 object by storing the data and calls.

This package provides functions for reading ontologies into R as lists and manipulating sets of ontological terms.

This package enhances the R Optimization Infrastructure (ROI) package with the Embedded Conic Solver (ECOS) for solving conic optimization problems.

This package provides functions for bitwise operations on integer vectors.

This package provides pure R tools to read BMP format images. It is currently limited to 8 bit greyscale images and 24, 32 bit (A)RGB images.

This package provides tools to create some specific Space-Filling Design (SFD) and to test their quality.

This package provides tools to generate a violin point plot, a combination of a violin/histogram plot and a scatter plot by offsetting points within a category based on their density using quasirandom noise.

Network Common Data Form (netCDF) files are widely used for scientific data. Library-level access in R is provided through packages RNetCDF and ncdf4. The package ncdfCF is built on top of RNetCDF and makes the data and its attributes available as a set of R6 classes that are informed by the Climate and Forecasting Metadata Conventions. Access to the data uses standard R subsetting operators and common function forms.

This package provides an interface to use SPARQL to pose SELECT or UPDATE queries to an end-point.

The zlog package offers functions to transform laboratory measurements into standardised z or z(log)-values. Therefore the lower and upper reference limits are needed. If these are not known they could be estimated from a given sample.

The empirical transition matrix (etm) package estimates the matrix of transition probabilities for any time-inhomogeneous multistate model with finite state space using the Aalen-Johansen estimator.

This package embeds the SQLite database engine in R and provides an interface compliant with the DBI package. The source for the SQLite engine is included.

This package provides flexible parametric models for time-to-event data, including the Royston-Parmar spline model, generalized gamma and generalized F distributions. Any user-defined parametric distribution can be fitted, given at least an R function defining the probability density or hazard. There are also tools for fitting and predicting from fully parametric multi-state models.

This package provides a suite of elliptic and related functions including Weierstrass and Jacobi forms. It also includes various tools for manipulating and visualizing complex functions.

This package interacts with a suite of web services for chemical information. Sources include: Alan Wood's Compendium of Pesticide Common Names, Chemical Identifier Resolver, ChEBI, Chemical Translation Service, ChemSpider, ETOX, Flavornet, NIST Chemistry WebBook, OPSIN, PubChem, SRS, Wikidata.

This package provides alluvial plots for ggplot2. Alluvial plots use variable-width ribbons and stacked bar plots to represent multi-dimensional or repeated-measures data with categorical or ordinal variables.

Quantile Regression Forests is a tree-based ensemble method for estimation of conditional quantiles. It is particularly well suited for high-dimensional data. Predictor variables of mixed classes can be handled.

This package implements nested cross-validation applied to the glmnet and caret packages. With glmnet this includes cross-validation of elastic net alpha parameter. A number of feature selection filter functions (t-test, Wilcoxon test, ANOVA, Pearson/Spearman correlation, random forest, ReliefF) for feature selection are provided and can be embedded within the outer loop of the nested CV. Nested CV can be also be performed with the caret package giving access to the large number of prediction methods available in caret.