ARpMMEC.sim  R Documentation 
This function simulates a censored response variable with autoregressive errors of order p
, with mixed effect and a established censoring rate. This function returns the censoring vector and censored response vector.
ARpMMEC.sim( m, x = NULL, z = NULL, tt = NULL, nj, beta, sigmae, D, phi, struc = "ARp", typeModel = "Normal", p.cens = 0, cens.type = "left", nu = NULL )
m 
Number of individuals 
x 
Design matrix of the fixed effects of order 
z 
Design matrix of the random effects of order 
tt 
Vector 
nj 
Vector 
beta 
Vector of values fixed effects. 
sigmae 
It's the value for sigma. 
D 
Covariance Matrix for the random effects. 
phi 
Vector of length 
struc 
Correlation structure. This must be one of 
typeModel 

p.cens 
Censoring level for the process. Default is 
cens.type 

nu 
degrees of freedom for tStudent distibution (nu > 0, maybe noninteger). 
returns list:
cc 
Vector of censoring indicators. 
y_cc 
Vector of responses censoring. 
## Not run: p.cens = 0.1 m = 10 D = matrix(c(0.049,0.001,0.001,0.002),2,2) sigma2 = 0.30 phi = 0.6 beta = c(1,2,1) nj=rep(4,10) tt=rep(1:4,length(nj)) x<matrix(runif(sum(nj)*length(beta),1,1),sum(nj),length(beta)) z<matrix(runif(sum(nj)*dim(D)[1],1,1),sum(nj),dim(D)[1]) data=ARpMMEC.sim(m,x,z,tt,nj,beta,sigma2,D,phi,struc="ARp",typeModel="Normal",p.cens) y<data$y_cc cc<data$cc ## End(Not run)
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