This package provides tools to infer the code style (which style rules are followed and which ones are not) from one package and use it to check another. This makes it easier to find and correct the most important problems first.

This package provides an environment for teaching "Financial Engineering and Computational Finance" and for managing chronological and calendar objects.

The bit64 package provides serializable S3 atomic 64 bit (signed) integers that can be used in vectors, matrices, arrays and data.frames. Methods are available for coercion from and to logicals, integers, doubles, characters and factors as well as many elementwise and summary functions. Many fast algorithmic operations such as match and order support interactive data exploration and manipulation and optionally leverage caching.

This package allows clinicians to predict the rate and severity of future acute exacerbation in Chronic Obstructive Pulmonary Disease (COPD) patients, based on the clinical prediction model published in Adibi et al. (2019) doi:10.1101/651901.

This package provides a dataset with an uneven number of cases in each class is said to be unbalanced. Many models produce a subpar performance on unbalanced datasets.

This package provides functions for cognitive diagnosis modeling and multidimensional item response modeling for dichotomous and polytomous item responses. It enables the estimation of the DINA and DINO model, the multiple group (polytomous) GDINA model, the multiple choice DINA model, the general diagnostic model (GDM), the structured latent class model (SLCA), and regularized latent class analysis. See George, Robitzsch, Kiefer, Gross, and Uenlue (2017) doi:10.18637/jss.v074.i02 for further details on estimation and the package structure. For tutorials on how to use the CDM package see George and Robitzsch (2015, doi:10.20982/tqmp.11.3.p189) as well as Ravand and Robitzsch (2015).

This package contains a number of common astronomy conversion routines, particularly the HMS and degrees schemes, which can be fiddly to convert between on mass due to the textural nature of the former. It allows users to coordinate match datasets quickly. It also contains functions for various cosmological calculations.

This package provides cross-platform utilities for prompting the user for credentials or a passphrase, for example to authenticate with a server or read a protected key.

This package provides a fast parallelized alternative to R's native dist function to calculate distance matrices for continuous, binary, and multi-dimensional input matrices, which supports a broad variety of predefined distance functions from other R packages, as well as user- defined functions written in C++. For ease of use, the parDist function extends the signature of the dist function and uses the same parameter naming conventions as distance methods of existing R packages.

Proto is an object oriented system using object-based, also called prototype-based, rather than class-based object oriented ideas.

This package can compute multivariate normal and t-probabilities, quantiles, random deviates and densities.

This package provides support for rendering of formatted text using Grid graphics. Text can be formatted via a minimal subset of Markdown, HTML, and inline CSS directives, and it can be rendered both with and without word wrap.

Similarity Network Fusion takes multiple views of a network and fuses them together to construct an overall status matrix. The input to our algorithm can be feature vectors, pairwise distances, or pairwise similarities. The learned status matrix can then be used for retrieval, clustering, and classification.

This package provides colour choice in information visualisation. It important in order to avoid being mislead by inherent bias in the used colour palette. This package provides access to the perceptually uniform and colour-blindness friendly palettes developed by Fabio Crameri and released under the "Scientific Colour-Maps" moniker. The package contains 24 different palettes and includes both diverging and sequential types.

This package contains a simple SMTP client which provides a portable solution for sending email, including attachments, from within R.

This package provides improved predictive models by indirect classification and bagging for classification, regression and survival problems as well as resampling based estimators of prediction error.

Hapassoc performs likelihood inference of trait associations with haplotypes and other covariates in generalized linear models (GLMs). The functions are developed primarily for data collected in cohort or cross-sectional studies. They can accommodate uncertain haplotype phase and handle missing genotypes at some SNPs.

This package contains extensions to ggplot2.

1. Geomas: geom_table, geom_plot and geom_grob add insets to plots using native data coordinates, while geom_table_npc, geom_plot_npc and geom_grob_npc do the same using npc coordinates through new aesthetics npcx and npcy.

2. Statistics: select observations based on 2D density.

3. Positions: radial nudging away from a center point and nudging away from a line or curve.

This package provides color palettes. They are checked for colorblind accessibility from hue, saturation, and lightness value scaling using the Chroma.js Color Palette Helper. See https://gka.github.io/palettes.

This package provides miscellaneous functions for SciViews or general use, including tools to manage a temporary environment attached to the search path for temporary variables you do not want to save() or load(); test the current platform; showing progress bars, etc.

This package provides a cross-platform solution to open files, directories or URLs with their associated programs.

This package implements multitaper spectral estimation techniques using prolate spheroidal sequences (Slepians) and sine tapers for time series analysis. It includes an adaptive weighted multitaper spectral estimate, a coherence estimate, Thomson's Harmonic F-test, and complex demodulation. The Slepians sequences are generated efficiently using a tridiagonal matrix solution, and jackknifed confidence intervals are available for most estimates.

This package provides basic functions, implemented in C, for large data manipulation. Fast vectorised ifelse()/nested if()/switch() functions, psum()/pprod() functions equivalent to pmin()/pmax() plus others which are missing from base R. Most of these functions are callable at C level.

A workflow is an object that can bundle together your pre-processing, modeling, and post-processing requests. For example, if you have a recipe and parsnip model, these can be combined into a workflow. The advantages are:

1. You don’t have to keep track of separate objects in your workspace.

2. The recipe prepping and model fitting can be executed using a single call to fit().

3. If you have custom tuning parameter settings, these can be defined using a simpler interface when combined with tune.

4. In the future, workflows will be able to add post-processing operations, such as modifying the probability cutoff for two-class models.