This package provides a set of functions to perform queries against the CCM API <https://mohcontacttracing.my.salesforce.com>.

This package provides iterators for combinations, permutations, subsets, and Cartesian product, which allow one to go through all elements without creating a huge set of all possible values.

Confirms if the number is Luhn compliant. Can check if credit card, IMEI number or any other Luhn based number is correct. For more info see: <https://en.wikipedia.org/wiki/Luhn_algorithm>.

Collection of routines for efficient scientific computations in physics and astrophysics. These routines include utility functions, numerical computation tools, as well as visualisation tools. They can be used, for example, for generating random numbers from spherical and custom distributions, information and entropy analysis, special Fourier transforms, two-point correlation estimation (e.g. as in Landy & Szalay (1993) <doi:10.1086/172900>), binning & gridding of point sets, 2D interpolation, Monte Carlo integration, vector arithmetic and coordinate transformations. Also included is a non-exhaustive list of important constants and cosmological conversion functions. The graphics routines can be used to produce and export publication-ready scientific plots and movies, e.g. as used in Obreschkow et al. (2020, MNRAS Vol 493, Issue 3, Pages 4551â 4569). These routines include special color scales, projection functions, and bitmap handling routines.

The cyclotomic numbers are complex numbers that can be thought of as the rational numbers extended with the roots of unity. They are represented exactly, enabling exact computations. They contain the Gaussian rationals (complex numbers with rational real and imaginary parts) as well as the square roots of all rational numbers. They also contain the sine and cosine of all rational multiples of pi. The algorithms implemented in this package are taken from the Haskell package cyclotomic', whose algorithms are adapted from code by Martin Schoenert and Thomas Breuer in the GAP project (<https://www.gap-system.org/>). Cyclotomic numbers have applications in number theory, algebraic geometry, algebraic number theory, coding theory, and in the theory of graphs and combinatorics. They have connections to the theory of modular functions and modular curves.

Compare C-statistics (concordance statistics) between two survival models, using either bootstrap resampling (Harrell's C) or Uno's C with perturbation-resampling (from the survC1 package). Returns confidence intervals and a p-value for the difference in C-statistics. Useful for evaluating and comparing predictive performance of survival models. Methods implemented for Uno's C are described in Uno et al. (2011) <doi:10.1002/sim.4154>.

Map functions while capturing results, errors, warnings, messages and other output tidily, then filter and summarise data frames or lists on the basis of those side effects.

Software to facilitates taking movement data in xyt format and pairing it with raster covariates within a continuous time Markov chain (CTMC) framework. As described in Hanks et al. (2015) <DOI:10.1214/14-AOAS803> , this allows flexible modeling of movement in response to covariates (or covariate gradients) with model fitting possible within a Poisson GLM framework.

Package to analyze the clinical utility of a biomarker. It provides the clinical utility curve, clinical utility table, efficacy of a biomarker, clinical efficacy curve and tests to compare efficacy between markers.

Functionality for segmenting individual trees from a forest stand scanned with a close-range (e.g., terrestrial or mobile) laser scanner. The complete workflow from a raw point cloud to a complete tabular forest inventory is provided. The package contains several algorithms for detecting tree bases and a graph-based algorithm to attach all remaining points to these tree bases. It builds heavily on the lidR package. A description of the segmentation algorithm can be found in Larysch et al. (2025) <doi:10.1007/s10342-025-01796-z>.

Cuddy-Della valle index gives the degree of instability present in the data by accommodating the effect of a trend. The adjusted R squared value of the best fitted model is chosen. The index is obtained by multiplying the coefficient of variation with square root of one minus the adjusted R-squared value. This package has been developed using concept of Shankar et al. (2022)<doi:10.3389/fsufs.2023.1208898>.

This package provides a tiny package to generate CRediT author statements (<https://credit.niso.org/>). It provides three functions: create a template, read it back and generate the CRediT author statement in a text file.

Defines the classes used for "class comparison" problems in the OOMPA project (<http://oompa.r-forge.r-project.org/>). Class comparison includes tests for differential expression; see Simon's book for details on typical problem types.

Clustering method to cluster both effects curves, through quantile regression coefficient modeling, and curves in functional data analysis. Sottile G. and Adelfio G. (2019) <doi:10.1007/s00180-018-0817-8>.

This package provides a suite of functions for rapid and flexible analysis of codon usage bias. It provides in-depth analysis at the codon level, including relative synonymous codon usage (RSCU), tRNA weight calculations, machine learning predictions for optimal or preferred codons, and visualization of codon-anticodon pairing. Additionally, it can calculate various gene- specific codon indices such as codon adaptation index (CAI), effective number of codons (ENC), fraction of optimal codons (Fop), tRNA adaptation index (tAI), mean codon stabilization coefficients (CSCg), and GC contents (GC/GC3s/GC4d). It also supports both standard and non-standard genetic code tables found in NCBI, as well as custom genetic code tables.

Classification of climate according to Koeppen - Geiger, of aridity indices, of continentality indices, of water balance after Thornthwaite, of viticultural bioclimatic indices. Drawing climographs: Thornthwaite, Peguy, Bagnouls-Gaussen.

Provide standard tables, listings, and graphs (TLGs) libraries used in clinical trials. This package implements a structure to reformat the data with dunlin', create reporting tables using rtables and tern with standardized input arguments to enable quick generation of standard outputs. In addition, it also provides comprehensive data checks and script generation functionality.

This package implements computationally-efficient construction of confidence intervals from permutation or randomization tests for simple differences in means, based on Nguyen (2009) <doi:10.15760/etd.7798>.

This package provides a set of tools to read, analyze and write lists of click sequences on websites (i.e., clickstream). A click can be represented by a number, character or string. Clickstreams can be modeled as zero- (only computes occurrence probabilities), first- or higher-order Markov chains.

This package contains the CONCOR (CONvergence of iterated CORrelations) algorithm and a series of supplemental functions for easy running, plotting, and blockmodeling. The CONCOR algorithm is used on social network data to identify network positions based off a definition of structural equivalence; see Breiger, Boorman, and Arabie (1975) <doi:10.1016/0022-2496(75)90028-0> and Wasserman and Faust's book Social Network Analysis: Methods and Applications (1994). This version allows multiple relationships for the same set of nodes and uses both incoming and outgoing ties to find positions.

Fit composite Gaussian process (CGP) models as described in Ba and Joseph (2012) "Composite Gaussian Process Models for Emulating Expensive Functions", Annals of Applied Statistics. The CGP model is capable of approximating complex surfaces that are not second-order stationary. Important functions in this package are CGP, print.CGP, summary.CGP, predict.CGP and plotCGP.

Typical morphological profiling datasets have millions of cells and hundreds of features per cell. When working with this data, you must clean the data, normalize the features to make them comparable across experiments, transform the features, select features based on their quality, and aggregate the single-cell data, if needed. cytominer makes these steps fast and easy. Methods used in practice in the field are discussed in Caicedo (2017) <doi:10.1038/nmeth.4397>. An overview of the field is presented in Caicedo (2016) <doi:10.1016/j.copbio.2016.04.003>.

Package to assess the calibration of probabilistic classifiers using confidence bands for monotonic functions. Besides testing the classical goodness-of-fit null hypothesis of perfect calibration, the confidence bands calculated within that package facilitate inverted goodness-of-fit tests whose rejection allows for a sought-after conclusion of a sufficiently well-calibrated model. The package creates flexible graphical tools to perform these tests. For construction details see also Dimitriadis, Dümbgen, Henzi, Puke, Ziegel (2022) <arXiv:2203.04065>.

Solves control systems problems relating to time/frequency response, LTI systems design and analysis, transfer function manipulations, and system conversion.