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.

The R package ggplot2 is a plotting system based on the grammar of graphics. GGally extends ggplot2 by adding several functions to reduce the complexity of combining geometric objects with transformed data. Some of these functions include a pairwise plot matrix, a two group pairwise plot matrix, a parallel coordinates plot, a survival plot, and several functions to plot networks.

This package provides tools to find the k nearest neighbours for every point in a given dataset in O(N log N) time using Arya and Mount's ANN library. There is support for approximate as well as exact searches, fixed radius searches and bd as well as kd trees. The distance is computed using the L1 (Manhattan, taxicab) metric.

This is a package for model fitting, optimal model selection and calculation of various features that are essential in the analysis of quantitative real-time polymerase chain reaction (qPCR).

This package provides maximally selected rank statistics with several p-value approximations.

This package provides functions for kernel-regression-based association tests including Burden test, SKAT and SKAT-O. These methods aggregate individual SNP score statistics in a SNP set and efficiently compute SNP-set level p-values.

This package lets you import OpenDocument Spreadsheet (ODS) into R as a data frame. It also supports writing data frames to an ODS file.

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 enables you to estimate the p-values for predictors x against target variable y in Lasso regression, using the regularization strength when each predictor enters the active set of regularization path for the first time as the statistic.

This package provides an interface to the rich display capabilities of Jupyter front-ends (e.g. Jupyter Notebook). It is designed to be used from a running IRkernel session.

This package provides a friendly interface for the construction of regular expressions. Regular expressions are a very powerful feature, however they are often difficult to interpret. Rex allows you to build complex regular expressions from human readable expressions

ICGE is a package that helps to estimate the number of real clusters in data as well as to identify atypical units. The underlying methods are based on distances rather than on unit x variables.

This package provides qualitatively constrained (regression) smoothing splines via linear programming and sparse matrices.

Subject recruitment for medical research is challenging. Slow patient accrual leads to delay in research. Accrual monitoring during the process of recruitment is critical. Researchers need reliable tools to manage the accrual rate. This package provides an implementation of a Bayesian method that integrates researcher's experience on previous trials and data from the current study, providing reliable prediction on accrual rate for clinical studies. It provides functions for Bayesian accrual prediction which can be easily used by statisticians and clinical researchers.

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

This package provides methods for calculating accurate numerical first and second order derivatives.

RestRserve is an R web API framework for building high-performance AND robust microservices and app backends. With Rserve backend on UNIX-like systems it is parallel by design. It will handle incoming requests in parallel - each request in a separate fork.

This package lets you compute and plot predictions, slopes, marginal means, and comparisons (contrasts, risk ratios, odds, etc.) for over 100 classes of statistical and machine learning models in R. Conduct linear and non-linear hypothesis tests, or equivalence tests. Calculate uncertainty estimates using the delta method, bootstrapping, or simulation-based inference. Details can be found in Arel-Bundock, Greifer, and Heiss (2024) <doi:10.18637/jss.v111.i09>.

This package defines S4 classes for single-cell genomic data and associated information, such as dimensionality reduction embeddings, nearest-neighbor graphs, and spatially-resolved coordinates. It provides data access methods and R-native hooks to ensure the Seurat object is familiar to other R users.

Kernel factory is an ensemble method where each base classifier (random forest) is fit on the kernel matrix of a subset of the training data.

This package contains an efficient implementation of Sen's slope method (Sen, 1968) plus implementation of Xuebin Zhang's (Zhang, 1999) and Yue-Pilon's (Yue, 2002) pre-whitening approaches to determining trends in climate data.

This package provides tools for fitting possibly high dimensional penalized regression models. The penalty structure can be any combination of an L1 penalty (lasso and fused lasso), an L2 penalty (ridge) and a positivity constraint on the regression coefficients. The supported regression models are linear, logistic and Poisson regression and the Cox Proportional Hazards model. Cross-validation routines allow optimization of the tuning parameters.

The pscl is an R package providing classes and methods for:

1. Bayesian analysis of roll call data (item-response models);

2. elementary Bayesian statistics;

3. maximum likelihood estimation of zero-inflated and hurdle models for count data;

4. utility functions.

This package helps you with creation and use of R repositories via helper functions to insert packages into a repository, and to add repository information to the current R session. Two primary types of repositories are supported: gh-pages at GitHub, as well as local repositories on either the same machine or a local network. Drat is a recursive acronym: Drat R Archive Template.