This package implements targeted minimum loss-based estimators of counterfactual means and causal effects that are doubly-robust with respect both to consistency and asymptotic normality.

This package provides all final tables of Germany's highest football league, the Bundesliga. It contains data from 1964 to 2016.

This package provides functions for simple fixed and random effects meta-analysis for two-sample comparisons and cumulative meta-analyses. It draws standard summary plots, funnel plots, and computes summaries and tests for association and heterogeneity.

This package provides an easy and simple way to read, write and display bitmap images stored in the TIFF format. It can read and write both files and in-memory raw vectors.

This package provides implementations of apply(), eapply(), lapply(), Map(), mapply(), replicate(), sapply(), tapply(), and vapply() that can be resolved using any future-supported backend, e.g. parallel on the local machine or distributed on a compute cluster.

This package computes standardized mean differences and confidence intervals for multiple data types based on Yang, D., & Dalton, J. E. (2012) <https://support.sas.com/resources/papers/proceedings12/335-2012.pdf>.

This package provides functions for fitting the entire solution path of the Elastic-Net and also provides functions for estimating sparse Principal Components. The Lasso solution paths can be computed by the same function.

This package provides a collection of efficient, vectorized algorithms for the creation and investigation of magic squares and hypercubes, including a variety of functions for the manipulation and analysis of arbitrarily dimensioned arrays.

This package provides an interface to Amazon Web Services networking and content delivery services, including Route 53 Domain Name System service, CloudFront content delivery, load balancing, and more.

This package provides a base S4 class for comparative methods, incorporating one or more trees and trait data.

This package provides functions for fitting and plotting SITAR growth curve models. SITAR is a shape- invariant model with a regression B-spline mean curve and subject-specific random effects on both the measurement and age scales.

This package is an extension to the testthat package that makes it easy to add graphical unit tests. It provides a Shiny application to manage the test cases.

This package provides functions to fit kernel density functions to data on temporal activity patterns of animals; estimate coefficients of overlapping of densities for two species; and calculate bootstrap estimates of confidence intervals.

This package provides a tool for calculating z-scores and centiles for weight-for-age, length/height-for-age, weight-for-length/height, BMI-for-age, head circumference-for-age, age circumference-for-age, subscapular skinfold-for-age, triceps skinfold-for-age based on the WHO Child Growth Standards.

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

This package contains an implementation of a function digest() for the creation of hash digests of arbitrary R objects (using the md5, sha-1, sha-256, crc32, xxhash and murmurhash algorithms) permitting easy comparison of R language objects, as well as a function hmac() to create hash-based message authentication code.

Please note that this package is not meant to be deployed for cryptographic purposes for which more comprehensive (and widely tested) libraries such as OpenSSL should be used.

This package provides empirical likelihood ratio tests for means/quantiles/hazards from possibly censored and/or truncated data. It also does regression.

For tree ensembles such as random forests, regularized random forests and gradient boosted trees, this package provides functions for: extracting, measuring and pruning rules; selecting a compact rule set; summarizing rules into a learner; calculating frequent variable interactions; formatting rules in latex code. Reference: Interpreting tree ensembles with inTrees (Houtao Deng, 2019, <doi:10.1007/s41060-018-0144-8>).

This package provides an R-based solution for symbolic differentiation. It admits user-defined functions as well as function substitution in arguments of functions to be differentiated. Some symbolic simplification is part of the work.

This package is meant to ease the creation of time-to-event (i.e. survival) endpoint figures. The modular functions create figures ready for publication. Each of the functions that add to or modify the figure are written as proper ggplot2 geoms or stat methods, allowing the functions from this package to be combined with any function or customization from ggplot2 and other ggplot2 extension packages.

Artificial Bee Colony (ABC) is one of the most recently defined algorithms by Dervis Karaboga in 2005, motivated by the intelligent behavior of honey bees. It is as simple as Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms, and uses only common control parameters such as colony size and maximum cycle number. The r-abcoptim implements the Artificial bee colony optimization algorithm http://mf.erciyes.edu.tr/abc/pub/tr06_2005.pdf. This version is a work-in-progress and is written in R code.

This package provides very fast read and write access to images stored in the NIfTI-1 and ANALYZE-7.5 formats, with seamless synchronisation between compiled C and interpreted R code. It also provides a C/C++ API that can be used by other packages.

This is an R package for imputing dropout events. Many statistical methods in cell type identification, visualization and lineage reconstruction do not account for dropout events. DrImpute can improve the performance of such software by imputing dropout events.

This package solves convex cone programs via operator splitting. It can solve: linear programs, second-order cone programs, semidefinite programs, exponential cone programs, and power cone programs, or problems with any combination of those cones. SCS uses AMD (a set of routines for permuting sparse matrices prior to factorization) and LDL (a sparse LDL factorization and solve package) from SuiteSparse.