SimGenCluster function

Simulation of clustered data

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

SimGenCluster(
  parC,
  parM,
  clu,
  xc = NULL,
  xm = NULL,
  family,
  rot = 0,
  dfC = NULL,
  model,
  dfM = NULL,
  offset = NULL
)

Arguments

• parC: vector of copula parameters; k1 is the number of covariates + constant for the copula
• parM: vector of margin parameters; k2 is the number of covariates + constant for the margins
• clu: vector of clusters (can be a factor)
• xc: matrix (N x k1) of covariates for the copula, not including the constant (can be NULL)
• xm: matrix (N x k2) 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 the Student copula (default is NULL)
• model: marginal distribution: "binomial" (bernoulli), "poisson", "nbinom" (mean is the parameter),"nbinom1" (p is the parameter), "geometric", "multinomial", exponential", "weibull", "normal" (gaussian),"t", "laplace"
• dfM: degrees of freedom for the Student margins (default is NULL)
• offset: offset for the margins (default is NULL)

Returns

• y: Simulated response

• y: Simulated values

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 = 0 # yields tau = 0.5 for Clayton
parM= c(1,-1,4)
xm = runif(N)
y=SimGenCluster(parC,parM,xm,family="clayton",rot=90,clu=clu,model="gaussian")

Author(s)

Bruno N. Remillard