SimMultinomial function

Simulation of multinomial clustered data

Generate a random sample of multinomial observations from a copula-based mixed regression model.

SimMultinomial(
  parC,
  parM,
  clu,
  xc = NULL,
  xm = NULL,
  family,
  rot = 0,
  dfC = NULL,
  offset = NULL
)

Arguments

• parC: copula parameters
• parM: matrix of dimension (L-1)x k2 of margin parameters; L is the number of levels and k2 is the number of covariates+constant for the margins
• clu: vector of clusters (can be a factor)
• xc: matrix of covariates for the copula, not including the constant (can be NULL)
• xm: matrix of covariates for the margins, not including the constant (can be NULL)
• family: copula family: "gaussian" , "t" , "clayton" , "joe", "frank" , "gumbel", "plackett"
• rot: rotation: 0 (default), 90, 180 (survival), or 270
• dfC: degrees of freedom for student copula (default is NULL)
• offset: offset for the margins (default is NULL)

Returns

• y: Simulated factor

Examples

K=50 #number of clusters
n=5  #size of each cluster
N=n*K
set.seed(1)
clu=rep(c(1:K),each=n)
parC = 2
parM=matrix(c(1,-1,0.5,2),byrow=TRUE,ncol=2)
xm = runif(N)
y=SimMultinomial(parC,parM,clu,xm=xm,family="clayton",rot=90)

Author(s)

Bruno N. Remillard