This is a package to compare sequence fragment lengths or molecular weights from pairs of lanes. The number of matching bands in the Restriction Fragment Length Polymorphism (RFLP) data is calculated using the align-and-count method.

This package provides header library and R functions to solve minimum cost bipartite matching problem using Huhn-Munkres algorithm (Hungarian algorithm; <https://en.wikipedia.org/wiki/Hungarian_algorithm>; Kuhn (1955) <doi:10.1002/nav.3800020109>).

This package provides tools to calculate the Earth Mover's Distance (EMD).

The ROI is a framework for handling optimization problems in R.

This package provides functions and vignettes to update data sets in Ecdat and to create, manipulate, plot, and analyze those and similar data sets.

This package provides full screen and partial loading screens for Shiny with spinners, progress bars, and notifications.

This R package caches the results of a function so that when you call it again with the same arguments it returns the pre-computed value.

This package provides cover-tree and kd-tree fast k-nearest neighbor search algorithms. Related applications including KNN classification, regression and information measures are implemented.

This package provides functions for kernel smoothing (and density estimation) corresponding to the book: Wand, M.P. and Jones, M.C. (1995) "Kernel Smoothing".

This package provides a header-only C++ library is provided with support for dates, time zones, ISO weeks, Julian dates, and Islamic dates. date offers extensive date and time functionality for the C++11, C++14 and C++17 standards. A slightly modified version has been accepted (along with tz.h) as part of C++20. This package regroups all header files from the upstream repository so that other R packages can use them in their C++ code.

This package provides functions to compute insolation on tilted surfaces, computes atmospheric transmittance and related parameters such as: Earth radius vector, declination, sunset and sunrise, daylength, equation of time, vector in the direction of the sun, vector normal to surface, and some atmospheric physics.

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 provides an implementation of maximum likelihood estimators for a variety of heavy tailed distributions, including both the discrete and continuous power law distributions. Additionally, a goodness-of-fit based approach is used to estimate the lower cut-off for the scaling region.

This package provides a collection of functions to explore and to investigate basic properties of financial returns and related quantities. The covered fields include techniques of explorative data analysis and the investigation of distributional properties, including parameter estimation and hypothesis testing. Even more, there are several utility functions for data handling and management.

This package computes various confidence intervals (CI) for the Kaplan-Meier estimator, namely: Petos CI, Rothman CI, CIs based on Greenwoods variance, Thomas and Grunkemeier CI and the simultaneous confidence bands by Nair and Hall and Wellner.

Group-Lasso INTERaction-NET. Fits linear pairwise-interaction models that satisfy strong hierarchy: if an interaction coefficient is estimated to be nonzero, then its two associated main effects also have nonzero estimated coefficients. Accommodates categorical variables (factors) with arbitrary numbers of levels, continuous variables, and combinations thereof. Implements the machinery described in the paper "Learning interactions via hierarchical group-lasso regularization" (JCGS 2015, Volume 24, Issue 3). Michael Lim & Trevor Hastie (2015)

This package provides bindings to the OSQP solver. The OSQP solver is a numerical optimization package or solving convex quadratic programs written in C and based on the alternating direction method of multipliers. See <arXiv:1711.08013> for details.

This package computes two-sample confidence intervals for single, paired and independent proportions.

This package provides authentication helpers for Snowflake. It provides compatibility with authentication approaches supported by the Snowflake Connector for Python and the Snowflake CLI.

This package provides an R interface to the GNU Linear Programming Kit, software for solving large-scale linear programming (LP), mixed integer linear programming (MILP) and other related problems.

This package provides methods to create, store, access, and manipulate large matrices. Matrices are allocated to shared memory and may use memory-mapped files.

This package provides functionality to assert conditions that have to be met so that errors in data used in analysis pipelines can fail quickly. It is similar to stopifnot() but more powerful, friendly, and easier for use in pipelines.

This package provides functions related to human natural ordering. It handles adjacent digits in a character sequence as a number so that natural sort function arranges a character vector by their numbers, not digit characters.

The C++ header files of the Stan project are provided by this package. There is a shared object containing part of the CVODES library, but it is not accessible from R. r-stanheaders is only useful for developers who want to utilize the LinkingTo directive of their package's DESCRIPTION file to build on the Stan library without incurring unnecessary dependencies.

The Stan project develops a probabilistic programming language that implements full or approximate Bayesian statistical inference via Markov Chain Monte Carlo or variational methods and implements (optionally penalized) maximum likelihood estimation via optimization. The Stan library includes an advanced automatic differentiation scheme, templated statistical and linear algebra functions that can handle the automatically differentiable scalar types (and doubles, ints, etc.), and a parser for the Stan language. The r-rstan package provides user-facing R functions to parse, compile, test, estimate, and analyze Stan models.