Other packages > Find by keyword >

SimMultiCorrData  

Simulation of Correlated Data with Multiple Variable Types
View on CRAN: Click here


Download and install SimMultiCorrData package within the R console
Install from CRAN:
install.packages("SimMultiCorrData")

Install from Github:
library("remotes")
install_github("cran/SimMultiCorrData")

Install by package version:
library("remotes")
install_version("SimMultiCorrData", "0.2.2")



Attach the package and use:
library("SimMultiCorrData")
Maintained by
Allison Cynthia Fialkowski
[Scholar Profile | Author Map]
First Published: 2017-06-30
Latest Update: 2018-06-28
Description:
Generate continuous (normal or non-normal), binary, ordinal, and count (Poisson or Negative Binomial) variables with a specified correlation matrix.It can also produce a single continuous variable.This package can be used to simulate data sets that mimic real-world situations (i.e. clinical or genetic data sets, plasmodes).All variables are generated from standard normal variables with an imposed intermediate correlation matrix.Continuous variables are simulated by specifying mean, variance, skewness, standardized kurtosis, and fifth and sixth standardized cumulants using either Fleishman's third-order (<doi:10.1007/BF02293811>) or Headrick's fifth-order (<doi:10.1016/S0167-9473(02)00072-5>) polynomial transformation.Binary and ordinal variables are simulated using a modification of the ordsample() function from 'GenOrd'. Count variables are simulated using the inverse cdf method.There are two simulation pathways which differ primarily according to the calculation of the intermediate correlation matrix.In Correlation Method 1, the intercorrelations involving count variables are determined using a simulation based, logarithmic correlation correction (adapting Yahav and Shmueli's 2012 method, <doi:10.1002/asmb.901>).In Correlation Method 2, the count variables are treated as ordinal (adapting Barbiero and Ferrari's 2015 modification of GenOrd, <doi:10.1002/asmb.2072>). There is an optional error loop that corrects the final correlation matrix to be within a user-specified precision value of the target matrix.The package also includes functions to calculate standardized cumulants for theoretical distributions or from real data sets, check if a target correlation matrix is within the possible correlation bounds (given the distributions of the simulated variables), summarize results (numerically or graphically), to verify valid power method pdfs, and to calculate lower standardized kurtosis bounds.
How to cite:
Allison Cynthia Fialkowski (2017). SimMultiCorrData: Simulation of Correlated Data with Multiple Variable Types. R package version 0.2.2, https://cran.r-project.org/web/packages/SimMultiCorrData. Accessed 30 Apr. 2025.
Previous versions and publish date:
0.1.0 (2017-06-30 00:44), 0.2.0 (2017-10-25 18:38), 0.2.1 (2017-11-09 19:12)
Other packages that cited SimMultiCorrData R package
View SimMultiCorrData citation profile
Other R packages that SimMultiCorrData depends, imports, suggests or enhances
Complete documentation for SimMultiCorrData
Functions, R codes and Examples using the SimMultiCorrData R package
Some associated functions: H_params . Headrick.dist . SimMultiCorrData . calc_final_corr . calc_fisherk . calc_lower_skurt . calc_moments . calc_theory . cdf_prob . chat_nb . chat_pois . denom_corr_cat . error_loop . error_vars . find_constants . findintercorr . findintercorr2 . findintercorr_cat_nb . findintercorr_cat_pois . findintercorr_cont . findintercorr_cont_cat . findintercorr_cont_nb . findintercorr_cont_nb2 . findintercorr_cont_pois . findintercorr_cont_pois2 . findintercorr_nb . findintercorr_pois . findintercorr_pois_nb . fleish . fleish_Hessian . fleish_skurt_check . intercorr_fleish . intercorr_poly . max_count_support . nonnormvar1 . ordnorm . pdf_check . plot_cdf . plot_pdf_ext . plot_pdf_theory . plot_sim_cdf . plot_sim_ext . plot_sim_pdf_ext . plot_sim_pdf_theory . plot_sim_theory . poly . poly_skurt_check . power_norm_corr . rcorrvar . rcorrvar2 . separate_rho . sim_cdf_prob . stats_pdf . valid_corr . valid_corr2 . var_cat . 
Some associated R codes: H_params-data.R . Headrick.dist-data.R . SimMultiCorrData.R . calc_final_corr.R . calc_fisherk.R . calc_lower_skurt.R . calc_moments.R . calc_theory.R . cdf_prob.R . chat_nb.R . chat_pois.R . denom_corr_cat.R . error_loop.R . error_vars.R . find_constants.R . findintercorr.R . findintercorr2.R . findintercorr_cat_nb.R . findintercorr_cat_pois.R . findintercorr_cont.R . findintercorr_cont_cat.R . findintercorr_cont_nb.R . findintercorr_cont_nb2.R . findintercorr_cont_pois.R . findintercorr_cont_pois2.R . findintercorr_nb.R . findintercorr_pois.R . findintercorr_pois_nb.R . fleish.R . fleish_Hessian.R . fleish_skurt_check.R . intercorr_fleish.R . intercorr_poly.R . max_count_support.R . nonnormvar1.R . ordnorm.R . pdf_check.R . plot_cdf.R . plot_pdf_ext.R . plot_pdf_theory.R . plot_sim_cdf.R . plot_sim_ext.R . plot_sim_pdf_ext.R . plot_sim_pdf_theory.R . plot_sim_theory.R . poly.R . poly_skurt_check.R . power_norm_corr.R . rcorrvar.R . rcorrvar2.R . separate_rho.R . sim_cdf_prob.R . stats_pdf.R . valid_corr.R . valid_corr2.R . var_cat.R .  Full SimMultiCorrData package functions and examples
Downloads during the last 30 days
03/3104/0104/0204/0304/0404/0504/0604/0704/0804/0904/1004/1104/1204/1304/1404/1504/1604/1704/1804/1904/2004/2104/2204/2304/2404/2504/2604/2704/28Downloads for SimMultiCorrData510152025303540455055TrendBars

Today's Hot Picks in Authors and Packages

GRAPE  
Gene-Ranking Analysis of Pathway Expression
Gene-Ranking Analysis of Pathway Expression (GRAPE) is a tool for summarizing the consensus behavio ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
schrute  
The Entire Transcript from the Office in Tidy Format
The complete scripts from the American version of the Office television show in tibble format. Use ...
Download / Learn more Package Citations See dependency  
eyetrackingR  
Eye-Tracking Data Analysis
Addresses tasks along the pipeline from raw data to analysis and visualization for eye-tracking dat ...
Download / Learn more Package Citations See dependency  
micEconAids  
Demand Analysis with the Almost Ideal Demand System (AIDS)
Functions and tools for analysing consumer demand with the Almost Ideal Demand System (AIDS) sugg ...
Download / Learn more Package Citations See dependency  
crimeutils  
A Comprehensive Set of Functions to Clean, Analyze, and Present Crime Data
A collection of functions that make it easier to understand crime (or other) data, and assist other ...
Download / Learn more Package Citations See dependency  

24,142

R Packages

207,311

Dependencies

65,176

Author Associations

24,143

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA