Como fazer seu código R ficar mais rápido com Rcpp
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Updated
Feb 3, 2022 - R
Como fazer seu código R ficar mais rápido com Rcpp
R Package: Adaptively weighted group lasso for semiparametic quantile regression models
Template for RcppArmadillo-dependent packages
GSOC 2021. R package that performs changepoint analysis using the Binary Segmentation algorithm. Supports several statistical distributions. The model is computed in C++ and then interfaced with R via the Rcpp package.
Classification using binary procrustes rotation
hmds: An R Package for Heuristic High and Multi Dimensional Scaling
This repo contains the codes in R and Cpp to replicate the original proposal of Linkletter for Bayesian Spatial Process Models for Social Network Analysis and our proposal using an estimation of the likelihood function.
R package that implements semiparametric binary response models in Klein and Spady (1993), built upon Rcpp along with OpenMP.
Statistical Learning, Machine Learning and Deep Learning algorithms
Bayesian Clustering of n-gons via a Double Dirichlet Mixture Model
Backpropagation for gradient descent in Rcpp for shallow artificial neural network
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.
R package bayessource: marginal likelihood and Bayes Factor computation for samples from Multivariate Gaussians
R wrappers for 'NGT' approximate nearest neighbor search
Different Applications of K-Means Clustering in Image Analysis
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