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jcrodriguez1989

rco:The R Code Optimizer

Automatically apply different strategies to optimize R code. 'rco' functions take R code as input, and returns R code as output.

Maintained by Juan Cruz Rodriguez. Last updated 4 months ago.

compilerfastgcchpcoptimizationoptimizer

11.0 match 82 stars 6.73 score

hongyuanjia

rdyncall:Improved Foreign Function Interface and Dynamic Bindings to C Libraries

Provides a cross-platform framework for dynamic binding of C libraries using a flexible Foreign Function Interface ('FFI'). The FFI supports almost all fundamental C types, multiple calling conventions, symbolic access to foreign C 'struct'/'union' data types and wrapping of R functions as C callback function pointers. Dynamic bindings to shared C libraries are data-driven by cross-platform binding specification using a compact plain text format; an initial repository of bindings to a couple of common C libraries ('OpenGL', 'SDL2', 'Expat', 'glew', 'CUDA', 'OpenCL', 'ODE', 'R') comes with the package. The package includes a variety of technology demos and OS-specific notes for installation of shared libraries.

Maintained by Hongyuan Jia. Last updated 2 years ago.

4.0 match 6 stars 3.84 score 23 scripts

stufield

gitr:A Lightweight API for 'Git'

A light-weight, dependency-free, application programming interface (API) to access system-level 'Git' commands from within 'R'. Contains wrappers and defaults for common data science workflows as well as 'Zsh' <https://github.com/ohmyzsh/ohmyzsh> plugin aliases. A generalized API syntax is also available. A system installation of 'Git' <https://git-scm.com/downloads> is required.

Maintained by Stu Field. Last updated 1 months ago.

gitzsh

3.3 match 1 stars 4.45 score 14 scripts

detlew

PowerTOST:Power and Sample Size for (Bio)Equivalence Studies

Contains functions to calculate power and sample size for various study designs used in bioequivalence studies. Use known.designs() to see the designs supported. Power and sample size can be obtained based on different methods, amongst them prominently the TOST procedure (two one-sided t-tests). See README and NEWS for further information.

Maintained by Detlew Labes. Last updated 12 months ago.

1.1 match 20 stars 9.61 score 112 scripts 4 dependents

rl1081

GCCfactor:GCC Estimation of the Multilevel Factor Model

Provides methods for model selection, estimation, bootstrap inference, and simulation for the multilevel factor model, based on the principal component estimation and generalised canonical correlation approach. Details can be found in "Generalised Canonical Correlation Estimation of the Multilevel Factor Model." Lin and Shin (2023) <doi:10.2139/ssrn.4295429>.

Maintained by Rui Lin. Last updated 1 years ago.

6.3 match 1.00 score

certara-jcraig

Certara.NLME8:Utilities for Certara's Nonlinear Mixed-Effects Modeling Engine

Perform Nonlinear Mixed-Effects (NLME) Modeling using Certara's NLME-Engine. Access the same Maximum Likelihood engines used in the Phoenix platform, including algorithms for parametric methods, individual, and pooled data analysis <https://www.certara.com/app/uploads/2020/06/BR_PhoenixNLME-v4.pdf>. The Quasi-Random Parametric Expectation-Maximization Method (QRPEM) is also supported <https://www.page-meeting.org/default.asp?abstract=2338>. Execution is supported both locally or on remote machines. Remote execution includes support for Linux Sun Grid Engine (SGE), Terascale Open-source Resource and Queue Manager (TORQUE) grids, Linux and Windows multicore, and individual runs.

Maintained by James Craig. Last updated 5 months ago.

1.8 match 2.65 score 3 dependents

jiaqihu2021

GrFA:Group Factor Analysis

Several group factor analysis algorithms are implemented, including Canonical Correlation-based Estimation by Choi et al. (2021) <doi:10.1016/j.jeconom.2021.09.008> , Generalised Canonical Correlation Estimation by Lin and Shin (2023) <doi:10.2139/ssrn.4295429>, Circularly Projected Estimation by Chen (2022) <doi:10.1080/07350015.2022.2051520>, and Aggregated projection method.

Maintained by Jiaqi Hu. Last updated 3 months ago.

3.3 match 1.30 score

eddelbuettel

sanitizers:C/C++ Source Code to Trigger Address and Undefined Behaviour Sanitizers

Recent gcc and clang compiler versions provide functionality to test for memory violations and other undefined behaviour; this is often referred to as "Address Sanitizer" (or 'ASAN') and "Undefined Behaviour Sanitizer" ('UBSAN'). The Writing R Extension manual describes this in some detail in Section 4.3 title "Checking Memory Access". . This feature has to be enabled in the corresponding binary, eg in R, which is somewhat involved as it also required a current compiler toolchain which is not yet widely available, or in the case of Windows, not available at all (via the common Rtools mechanism). . As an alternative, pre-built Docker containers such as the Rocker container 'r-devel-san' or the multi-purpose container 'r-debug' can be used. . This package then provides a means of testing the compiler setup as the known code failures provides in the sample code here should be detected correctly, whereas a default build of R will let the package pass. . The code samples are based on the examples from the Address Sanitizer Wiki at <https://github.com/google/sanitizers/wiki>.

Maintained by Dirk Eddelbuettel. Last updated 4 months ago.

cpp

0.5 match 11 stars 4.22 score 7 scripts

neuhausi

canvasXpress.data:Datasets for the 'canvasXpress' Package

Contains the prepared data that is needed for the 'shiny' application examples in the 'canvasXpress' package. This package also includes datasets used for automated 'testthat' tests. Scotto L, Narayan G, Nandula SV, Arias-Pulido H et al. (2008) <doi:10.1002/gcc.20577>. Davis S, Meltzer PS (2007) <doi:10.1093/bioinformatics/btm254>.

Maintained by Connie Brett. Last updated 4 years ago.

0.5 match 1 stars 3.48 score 3 scripts

profyliu

brif:A Tree and Forest Tool for Classification and Regression

Build decision trees and random forests for classification and regression. The implementation strikes a balance between minimizing computing efforts and maximizing the expected predictive accuracy, thus scales well to large data sets. Multi-threading is available through 'OpenMP' <https://gcc.gnu.org/wiki/openmp>.

Maintained by Yanchao Liu. Last updated 2 years ago.

cppopenmp

0.5 match 1.00 score

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