| genPBONdata {PoisBinOrdNor} | R Documentation |
Generates correlated data with multiple count, binary, ordinal and normal variables
Description
This function simulates a multivariate data set that is composed of count, binary, ordinal and normal variables with specified marginals and a correlation matrix.
Usage
genPBONdata(n, no_pois, no_bin, no_ord, no_norm, inter.mat, lamvec, prop_vec_bin,
prop_vec_ord, nor.mean, nor.var)
Arguments
n |
Number of rows |
no_pois |
Number of count variables |
no_bin |
Number of binary variables |
no_ord |
Number of ordinal variables |
no_norm |
Number of normal variables |
inter.mat |
The intermediate correlation matrix obtained from function intermat |
lamvec |
A vector of marginal rates for the count variables |
prop_vec_bin |
A vector of probabilities for the binary variables |
prop_vec_ord |
A vector of probabilities for the ordinal variables. For each of the variable, the i-th element of the pvec is the cumulative probability defining the marginal distribution of the ordinal variable. If the variable has k categories, the i-th element of p will contain k-1 probabilities. The k-th element is implicitly 1. |
nor.mean |
A vector of means for the normal variables |
nor.var |
A vector of variances for the normal variables |
Value
data |
A simulated data matrix of size nx(no_pois + no_bin + no_ord + no_norm), of which the first no_pois are count variables, followed by no_bin binary variables, no_ord ordinal variables, and lastly no_norm normal variables. |
n.rows |
Number of rows in the simulated data |
prob.bin |
A vector of probabilities for the binary variables |
prob.ord |
A vector of probabilities for the ordinal variables |
nor.mean |
A vector of means for the normal variables |
nor.var |
A vector of variances for the normal variables |
lamvec |
A vector of rate parameters for the count variables |
n.pois |
Number of count variables |
n.bin |
Number of binary variables |
n.ord |
Number of ordinal variables |
n.norm |
Number of normal variables |
final.corr |
The final correlation matrix for the simulated data |
Examples
## Not run:
ss=10000
num_pois<-2
num_bin<-1
num_ord<-2
num_norm<-1
lamvec=sample(10,2)
pbin=runif(1)
pord=list(c(0.1, 0.9), c(0.2, 0.3, 0.5))
nor.mean=3.1
nor.var=0.85
M=c(-0.05, 0.26, 0.14, 0.09, 0.14, 0.12, 0.13, -0.02, 0.17, 0.29,
-0.04, 0.19, 0.10, 0.35, 0.39)
N=diag(6)
N[lower.tri(N)]=M
TV=N+t(N)
diag(TV)<-1
intmat<-intermat(num_pois,num_bin,num_ord,num_norm,corr_mat=TV,pbin,pord,lamvec,
nor.mean,nor.var)
genPBONdata(ss,num_pois,num_bin,num_ord,num_norm,intmat,lamvec,pbin,pord,nor.mean,nor.var)
## End(Not run)