SimGenCluster {CopulaGAMM}

Simulation of clustered data

Description

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

Usage

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)

Value

y

Simulated response

y

Simulated values

Author(s)

Bruno N. Remillard

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")