CRAN/E | SimJoint

SimJoint

Simulate Joint Distribution

Installation

About

Simulate multivariate correlated data given nonparametric marginals and their joint structure characterized by a Pearson or Spearman correlation matrix. The simulator engages the problem from a purely computational perspective. It assumes no statistical models such as copulas or parametric distributions, and can approximate the target correlations regardless of theoretical feasibility. The algorithm integrates and advances the Iman-Conover (1982) approach doi:10.1080/03610918208812265 and the Ruscio-Kaczetow iteration (2008) doi:10.1080/00273170802285693. Package functions are carefully implemented in C++ for squeezing computing speed, suitable for large input in a manycore environment. Precision of the approximation and computing speed both substantially outperform various CRAN packages to date. Benchmarks are detailed in function examples. A simple heuristic algorithm is additionally designed to optimize the joint distribution in the post-simulation stage. The heuristic demonstrated good potential of achieving the same level of precision of approximation without the enhanced Iman-Conover-Ruscio-Kaczetow. The package contains a copy of Permuted Congruential Generator from .

System requirements GNU make

Key Metrics

Version 0.3.9
Published 2021-12-09 721 days ago
Needs compilation? yes
License GPL-3
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Maintainer

Maintainer

Charlie Wusuo Liu

liuwusuo@gmail.com

Authors

Charlie Wusuo Liu

Material

NEWS
Reference manual
Package source

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Distributions

Vignettes

SimulatedJointDistribution

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

SimJoint archive

Imports

Rcpp ≥ 1.0.0
RcppParallel

Suggests

R.rsp

LinkingTo

Rcpp
RcppParallel
RcppArmadillo