R-universe search: topic:armadillo

Showing 13 of total 13 results (show query)

rcppcore

RcppArmadillo:'Rcpp' Integration for the 'Armadillo' Templated Linear Algebra Library

'Armadillo' is a templated C++ linear algebra library (by Conrad Sanderson) that aims towards a good balance between speed and ease of use. Integer, floating point and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with LAPACK and ATLAS libraries. The 'RcppArmadillo' package includes the header files from the templated 'Armadillo' library. Thus users do not need to install 'Armadillo' itself in order to use 'RcppArmadillo'. From release 7.800.0 on, 'Armadillo' is licensed under Apache License 2; previous releases were under licensed as MPL 2.0 from version 3.800.0 onwards and LGPL-3 prior to that; 'RcppArmadillo' (the 'Rcpp' bindings/bridge to Armadillo) is licensed under the GNU GPL version 2 or later, as is the rest of 'Rcpp'.

Maintained by Dirk Eddelbuettel. Last updated 4 days ago.

armadillo c-plus-plus rcpp rcpparmadillo openblas cpp openmp

200 stars 18.85 score 1.9k scripts 3.4k dependents

pachadotdev

cpp11armadillo:An 'Armadillo' Interface

Provides function declarations and inline function definitions that facilitate communication between R and the 'Armadillo' 'C++' library for linear algebra and scientific computing. This implementation is detailed in Vargas Sepulveda and Schneider Malamud (2024) <doi:10.1016/j.softx.2025.102087>.

Maintained by Mauricio Vargas Sepulveda. Last updated 12 days ago.

armadillo cpp cpp11 hacktoberfest linear-algebra

10 stars 9.25 score 1 scripts 16 dependents

graemeleehickey

joineRML:Joint Modelling of Multivariate Longitudinal Data and Time-to-Event Outcomes

Fits the joint model proposed by Henderson and colleagues (2000) <doi:10.1093/biostatistics/1.4.465>, but extended to the case of multiple continuous longitudinal measures. The time-to-event data is modelled using a Cox proportional hazards regression model with time-varying covariates. The multiple longitudinal outcomes are modelled using a multivariate version of the Laird and Ware linear mixed model. The association is captured by a multivariate latent Gaussian process. The model is estimated using a Monte Carlo Expectation Maximization algorithm. This project was funded by the Medical Research Council (Grant number MR/M013227/1).

Maintained by Graeme L. Hickey. Last updated 2 months ago.

armadillo biostatistics clinical-trials cox dynamic joint-models longitudinal-data multivariate-analysis multivariate-data multivariate-longitudinal-data prediction rcpp regression-models statistics survival openblas cpp openmp

30 stars 8.93 score 146 scripts 1 dependents

coatless-rpkg

RcppEnsmallen:Header-Only C++ Mathematical Optimization Library for 'Armadillo'

'Ensmallen' is a templated C++ mathematical optimization library (by the 'MLPACK' team) that provides a simple set of abstractions for writing an objective function to optimize. Provided within are various standard and cutting-edge optimizers that include full-batch gradient descent techniques, small-batch techniques, gradient-free optimizers, and constrained optimization. The 'RcppEnsmallen' package includes the header files from the 'Ensmallen' library and pairs the appropriate header files from 'armadillo' through the 'RcppArmadillo' package. Therefore, users do not need to install 'Ensmallen' nor 'Armadillo' to use 'RcppEnsmallen'. Note that 'Ensmallen' is licensed under 3-Clause BSD, 'Armadillo' starting from 7.800.0 is licensed under Apache License 2, 'RcppArmadillo' (the 'Rcpp' bindings/bridge to 'Armadillo') is licensed under the GNU GPL version 2 or later. Thus, 'RcppEnsmallen' is also licensed under similar terms. Note that 'Ensmallen' requires a compiler that supports 'C++14' and 'Armadillo' 10.8.2 or later.

Maintained by James Joseph Balamuta. Last updated 4 months ago.

armadillo cpp11 ensmallen optimization rcpp rcpparmadillo openblas cpp openmp

31 stars 7.67 score 1 scripts 14 dependents

mlampros

elmNNRcpp:The Extreme Learning Machine Algorithm

Training and predict functions for Single Hidden-layer Feedforward Neural Networks (SLFN) using the Extreme Learning Machine (ELM) algorithm. The ELM algorithm differs from the traditional gradient-based algorithms for very short training times (it doesn't need any iterative tuning, this makes learning time very fast) and there is no need to set any other parameters like learning rate, momentum, epochs, etc. This is a reimplementation of the 'elmNN' package using 'RcppArmadillo' after the 'elmNN' package was archived. For more information, see "Extreme learning machine: Theory and applications" by Guang-Bin Huang, Qin-Yu Zhu, Chee-Kheong Siew (2006), Elsevier B.V, <doi:10.1016/j.neucom.2005.12.126>.

Maintained by Lampros Mouselimis. Last updated 2 years ago.

armadillo elm extreme-learning-machine rcpparmadillo openblas cpp openmp

14 stars 7.06 score 39 scripts 7 dependents

ypan1988

roptim:General Purpose Optimization in R using C++

Perform general purpose optimization in R using C++. A unified wrapper interface is provided to call C functions of the five optimization algorithms ('Nelder-Mead', 'BFGS', 'CG', 'L-BFGS-B' and 'SANN') underlying optim().

Maintained by Yi Pan. Last updated 3 years ago.

armadillo bfgs conjugate-gradient l-bfgs-b nelder-mead optim rcpp simulated-annealing openblas cpp

20 stars 6.93 score 15 scripts 12 dependents

coatless-rpkg

rgen:Random Sampling Distribution C++ Routines for Armadillo

Provides popular sampling distributions C++ routines based in armadillo through a header file approach.

Maintained by James Joseph Balamuta. Last updated 1 years ago.

armadillo random-distributions rcpp rcpparmadillo

4 stars 5.38 score 1 scripts 4 dependents

tmsalab

cIRT:Choice Item Response Theory

Jointly model the accuracy of cognitive responses and item choices within a Bayesian hierarchical framework as described by Culpepper and Balamuta (2015) <doi:10.1007/s11336-015-9484-7>. In addition, the package contains the datasets used within the analysis of the paper.

Maintained by James Joseph Balamuta. Last updated 3 years ago.

armadillo bayesian choice cognitive-diagnostic-models gibbs-sampling item-response-theory rcpparmadillo openblas cpp openmp

4 stars 5.14 score 23 scripts

tmsalab

dina:Bayesian Estimation of DINA Model

Estimate the Deterministic Input, Noisy "And" Gate (DINA) cognitive diagnostic model parameters using the Gibbs sampler described by Culpepper (2015) <doi:10.3102/1076998615595403>.

Maintained by James Joseph Balamuta. Last updated 5 years ago.

armadillo bayesian gibbs-sampler irt item-response-theory psychometrics rcpp rcpparmadillo openblas cpp

14 stars 3.85 score 3 scripts

tmsalab

iccbeta:Multilevel Model Intraclass Correlation for Slope Heterogeneity

A function and vignettes for computing an intraclass correlation described in Aguinis & Culpepper (2015) <doi:10.1177/1094428114563618>. This package quantifies the share of variance in a dependent variable that is attributed to group heterogeneity in slopes.

Maintained by Steven Andrew Culpepper. Last updated 5 years ago.

armadillo correlation intraclass-correlation rcpp rcpparmadillo openblas cpp

2 stars 3.00 score 5 scripts

tmsalab

rrum:Bayesian Estimation of the Reduced Reparameterized Unified Model with Gibbs Sampling

Implementation of Gibbs sampling algorithm for Bayesian Estimation of the Reduced Reparameterized Unified Model ('rrum'), described by Culpepper and Hudson (2017) <doi: 10.1177/0146621617707511>.

Maintained by James Joseph Balamuta. Last updated 1 years ago.

armadillo cdm cognitive-diagnostic-models gibbs-sampling-algorithm psychometrics rcpparmadillo rrum openblas cpp openmp

2.70 score 3 scripts

tmsalab

fourPNO:Bayesian 4 Parameter Item Response Model

Estimate Barton & Lord's (1981) <doi:10.1002/j.2333-8504.1981.tb01255.x> four parameter IRT model with lower and upper asymptotes using Bayesian formulation described by Culpepper (2016) <doi:10.1007/s11336-015-9477-6>.

Maintained by Steven Andrew Culpepper. Last updated 5 years ago.

armadillo cognitive-diagnostic-models gibbs-sampler item-response-theory rcpp rcpparmadillo openblas cpp openmp

1 stars 2.70 score 5 scripts

eddelbuettel

naarma:Connect nanoarrow with (Rcpp)Armadillo

The nanoarrow package offers C-level functionality to work with Arrow object, along with a small amount of C++ integration. This package uses it to interact with Armadillo objects. Some auxiliary testing facility from the nanoarrow package is included here as well.

Maintained by Dirk Eddelbuettel. Last updated 3 months ago.

armadillo arrow cpp mlpack cpp

2.00 score 4 scripts