genmvnorm {gendata} | R Documentation |
Genmvnorm
Description
Generates a multivariate normal dataset based on a specified correlation matrix.
Usage
genmvnorm(cor, k, n, seed = FALSE)
Arguments
cor |
Can be a correlation matrix– e.g., data<-cor(xyz)– or the lower half of a correlation matrix, e.g., for a 3 variable dataset, data<-c(.7,.3,.2)– useful for creating datasets without having to specify both halves of the correlation matrix. |
k |
Indicate the number of variables in your dataset. |
n |
Indicate the number of observations in your new synthetic dataset. |
seed |
For reproducability of results, set a specific seed number. |
Details
For creating synthetic datasets. Based on the SAS chapter by Fan et al. (2002).
Author(s)
Francis Huang
References
Based on:
Fan, X., Felsovalyi, A., Sivo, S., & Keenan, S. (2002). SAS for Monte Carlo studies: A guide for quantitative researchers. SAS Institute.
See Also
Examples
sdata<-genmvnorm(cor=c(.7,.2,.3),k=3,n=500,seed=12345)
cor(sdata)
#dataset above uses the lower half of a correlation table
# 1 .7 .2
# .7 1 .3
# .2 .3 1
# Can also use a correlation table
data(iris)
dat<-cor(iris[,1:3])
dat
sdata<-genmvnorm(cor=dat,k=3,n=100,seed=123)
cor(sdata)
#example above uses the IRIS dataset.
[Package gendata version 1.2.0 Index]