This package provides a simple set of wrapper functions for data.table::fread() that allows subsetting or filtering rows and selecting columns of table-formatted files too large for the available RAM.

This package provides convenience functions for advanced linear algebra with tensors and computation with datasets of tensors on a higher level abstraction. It includes Einstein and Riemann summing conventions, dragging, co- and contravariate indices, and parallel computations on sequences of tensors.

This package provides a complete analysis pipeline for matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) and other two-dimensional mass spectrometry data. In addition to commonly used plotting and processing methods it includes distinctive features, namely baseline subtraction methods such as morphological filters (TopHat) or the statistics-sensitive non-linear iterative peak-clipping algorithm (SNIP), peak alignment using warping functions, handling of replicated measurements as well as allowing spectra with different resolutions.

How fast can you type R functions on your keyboard? Find out by running a zty.pe game: export R functions as instructions to type to destroy opponents' vessels.

Joyplots provide a convenient way of visualizing changes in distributions over time or space. This package enables the creation of such plots in ggplot2.

This package provides tools to parse simple .ini configuration files to an structured list. Users can manipulate this resulting list with lapply() functions. This same structured list can be used to write back to file after modifications.

This package computes moments of univariate truncated T distribution. There is only one exported function, e_trunct, which should be seen for details.

This package implements multiple performance measures for supervised learning. It includes over 40 measures for regression and classification. Additionally, meta information about the performance measures can be queried, e.g. what the best and worst possible performances scores are.

Unlike other tools that dynamically link to the Cairo stack, freetypeharfbuzz is statically linked to specific versions of the FreeType and harfbuzz libraries. This ensures deterministic computation of text box extents for situations where reproducible results are crucial (for instance unit tests of graphics).

This package supplies tools for tabulating and analyzing the results of predictive models. The methods employed are applicable to virtually any predictive model and make comparisons between different methodologies straightforward.

This tool provides methods for aggregating ranked lists, especially lists of genes. It implements the Robust Rank Aggregation and other simple algorithms for the task. RRA method uses a probabilistic model for aggregation that is robust to noise and also facilitates the calculation of significance probabilities for all the elements in the final ranking.

This package lets you fit a variety of Bayesian latent variable models, including confirmatory factor analysis, structural equation models, and latent growth curve models.

This package is a usability wrapper around snow for easier development of parallel R programs. This package offers e.g. extended error checks, and additional functions. All functions work in sequential mode, too, if no cluster is present or wished. The package is also designed as connector to the cluster management tool sfCluster, but can also used without it.

This package is a toolkit for working with Bezier curves and splines. The package provides functions for point generation, arc length estimation, degree elevation and curve fitting.

This R package provides functions to create formattable vectors and data frames. Formattable vectors are printed with text formatting, and formattable data frames are printed with multiple types of formatting in HTML to improve the readability of data presented in tabular form rendered in web pages.

This package provides a set of predicates and assertions for checking the properties of matrices. This is mainly for use by other package developers who want to include run-time testing features in their own packages.

The Rmisc library contains functions for data analysis and utility operations.

Partial application is the process of reducing the arity of a function by fixing one or more arguments, thus creating a new function lacking the fixed arguments. The curry package provides three different ways of performing partial function application by fixing arguments from either end of the argument list (currying and tail currying) or by fixing multiple named arguments (partial application). This package provides this functionality through the %<%, %-<%, and %><% operators which allows for a programming style comparable to modern functional languages. Compared to other implementations such a purrr::partial() the operators in curry composes functions with named arguments, aiding in autocomplete etc.

This package provides a fast implementation of hierarchical clustering.

This package provides tools for the analysis and visualization of bilateral asymmetry in parasitic infections.

This package implements data manipulation methods such as cast, aggregate, and merge/join for Matrix and Matrix-like objects.

The smurf package contains the implementation of the Sparse Multi-type Regularized Feature (SMuRF) modeling algorithm to fit generalized linear models (GLMs) with multiple types of predictors via regularized maximum likelihood. Next to the fitting procedure, following functionality is available:

• Selection of the regularization tuning parameter lambda using three different approaches: in-sample, out-of-sample or using cross-validation.

• S3 methods to handle the fitted object including visualization of the coefficients and a model summary.

Algebraic procedures for analyses of multiple social networks are delivered with this package. multiplex makes possible, among other things, to create and manipulate multiplex, multimode, and multilevel network data with different formats. Effective ways are available to treat multiple networks with routines that combine algebraic systems like the partially ordered semigroup with decomposition procedures or semiring structures with the relational bundles occurring in different types of multivariate networks. multiplex provides also an algebraic approach for affiliation networks through Galois derivations between families of the pairs of subsets in the two domains of the network with visualization options.

This package provides a common interface to specifying clustering models, in the same style as parsnip. It creates a unified interface across different functions and computational engines.