cubature - Adaptive Multivariate Integration over Hypercubes

R wrappers around the cubature C library of Steven G. Johnson for adaptive multivariate integration over hypercubes and the Cuba C library of Thomas Hahn for deterministic and Monte Carlo integration. Scalar and vector interfaces for cubature and Cuba routines are provided; the vector interfaces are highly recommended as demonstrated in the package vignette.

Last updated 4 months ago

11.01 score 12 stars 153 packages 456 scripts 20k downloads

osqp - Quadratic Programming Solver using the 'OSQP' Library

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 <doi:10.48550/arXiv.1711.08013> for details.

Last updated 6 months ago

admmconvex-optimizationlassomachine-learningoperator-splittingquadratic-programming

8.18 score 12 stars 65 packages 40 scripts 11k downloads

ECOSolveR - Embedded Conic Solver in R

R interface to the Embedded COnic Solver (ECOS), an efficient and robust C library for convex problems. Conic and equality constraints can be specified in addition to integer and boolean variable constraints for mixed-integer problems. This R interface is inspired by the python interface and has similar calling conventions.

Last updated 6 months ago

7.83 score 5 stars 59 packages 30 scripts 5.1k downloads

clarabel - Interior Point Conic Optimization Solver

A versatile interior point solver that solves linear programs (LPs), quadratic programs (QPs), second-order cone programs (SOCPs), semidefinite programs (SDPs), and problems with exponential and power cone constraints (<https://clarabel.org/stable/>). For quadratic objectives, unlike interior point solvers based on the standard homogeneous self-dual embedding (HSDE) model, Clarabel handles quadratic objective without requiring any epigraphical reformulation of its objective function. It can therefore be significantly faster than other HSDE-based solvers for problems with quadratic objective functions. Infeasible problems are detected using using a homogeneous embedding technique.

Last updated 3 months ago

7.75 score 10 stars 35 packages 4 scripts 5.4k downloads

PMA - Penalized Multivariate Analysis

Performs Penalized Multivariate Analysis: a penalized matrix decomposition, sparse principal components analysis, and sparse canonical correlation analysis, described in Witten, Tibshirani and Hastie (2009) <doi:10.1093/biostatistics/kxp008> and Witten and Tibshirani (2009) Extensions of sparse canonical correlation analysis, with applications to genomic data <doi:10.2202/1544-6115.1470>.

Last updated 10 months ago

7.23 score 4 stars 11 packages 245 scripts 1.1k downloads

pamr - Pam: Prediction Analysis for Microarrays

Some functions for sample classification in microarrays.

Last updated 5 months ago

6.87 score 14 packages 241 scripts 7.3k downloads

homomorpheR - Homomorphic Computations in R

Homomorphic computations in R for privacy-preserving applications. Currently only the Paillier Scheme is implemented.

Last updated 3 years ago

5.73 score 4 stars 1 packages 18 scripts 173 downloads

deconvolveR - Empirical Bayes Estimation Strategies

Empirical Bayes methods for learning prior distributions from data. An unknown prior distribution (g) has yielded (unobservable) parameters, each of which produces a data point from a parametric exponential family (f). The goal is to estimate the unknown prior ("g-modeling") by deconvolution and Empirical Bayes methods. Details and examples are in the paper by Narasimhan and Efron (2020, <doi:10.18637/jss.v094.i11>).

Last updated 4 years ago

5.43 score 9 stars 2 packages 8 scripts 391 downloads

distcomp - Computations over Distributed Data without Aggregation

Implementing algorithms and fitting models when sites (possibly remote) share computation summaries rather than actual data over HTTP with a master R process (using 'opencpu', for example). A stratified Cox model and a singular value decomposition are provided. The former makes direct use of code from the R 'survival' package. (That is, the underlying Cox model code is derived from that in the R 'survival' package.) Sites may provide data via several means: CSV files, Redcap API, etc. An extensible design allows for new methods to be added in the future and includes facilities for local prototyping and testing. Web applications are provided (via 'shiny') for the implemented methods to help in designing and deploying the computations.

Last updated 5 months ago

5.33 score 9 stars 47 scripts 281 downloads

bcaboot - Bias Corrected Bootstrap Confidence Intervals

Computation of bootstrap confidence intervals in an almost automatic fashion as described in Efron and Narasimhan (2020, <doi:10.1080/10618600.2020.1714633>).

Last updated 4 years ago

5.18 score 17 stars 2 packages 15 scripts 390 downloads

ASSISTant - Adaptive Subgroup Selection in Group Sequential Trials

Clinical trial design for subgroup selection in three-stage group sequential trial. Includes facilities for design, exploration and analysis of such trials. An implementation of the initial DEFUSE-3 trial is also provided as a vignette.

Last updated 5 years ago

4.54 score 23 scripts 331 downloads

conTree - Contrast Trees and Boosting

Contrast trees represent a new approach for assessing the accuracy of many types of machine learning estimates that are not amenable to standard (cross) validation methods; see "Contrast trees and distribution boosting", Jerome H. Friedman (2020) <doi:10.1073/pnas.1921562117>. In situations where inaccuracies are detected, boosted contrast trees can often improve performance. Functions are provided to to build such trees in addition to a special case, distribution boosting, an assumption free method for estimating the full probability distribution of an outcome variable given any set of joint input predictor variable values.

Last updated 1 years ago

3.95 score 18 scripts 172 downloads

piqp - R Interface to Proximal Interior Point Quadratic Programming Solver

An embedded proximal interior point quadratic programming solver, which can solve dense and sparse quadratic programs, described in Schwan, Jiang, Kuhn, and Jones (2023) <doi:10.48550/arXiv.2304.00290>. Combining an infeasible interior point method with the proximal method of multipliers, the algorithm can handle ill-conditioned convex quadratic programming problems without the need for linear independence of the constraints. The solver is written in header only 'C++ 14' leveraging the 'Eigen' library for vectorized linear algebra. For small dense problems, vectorized instructions and cache locality can be exploited more efficiently. Allocation free problem updates and re-solves are also provided.

Last updated 1 years ago

3.74 score 11 scripts 154 downloads

multiview - Cooperative Learning for Multi-View Analysis

Cooperative learning combines the usual squared error loss of predictions with an agreement penalty to encourage the predictions from different data views to agree. By varying the weight of the agreement penalty, we get a continuum of solutions that include the well-known early and late fusion approaches. Cooperative learning chooses the degree of agreement (or fusion) in an adaptive manner, using a validation set or cross-validation to estimate test set prediction error. In the setting of cooperative regularized linear regression, the method combines the lasso penalty with the agreement penalty (Ding, D., Li, S., Narasimhan, B., Tibshirani, R. (2021) <doi:10.1073/pnas.2202113119>).

Last updated 2 years ago

2.85 score 14 scripts 173 downloads

banditpam - Almost Linear-Time k-Medoids Clustering

Interface to a high-performance implementation of k-medoids clustering described in Tiwari, Zhang, Mayclin, Thrun, Piech and Shomorony (2020) "BanditPAM: Almost Linear Time k-medoids Clustering via Multi-Armed Bandits" <https://proceedings.neurips.cc/paper/2020/file/73b817090081cef1bca77232f4532c5d-Paper.pdf>.

Last updated 2 years ago

2.74 score 11 scripts 191 downloads