# ARpLMEC.sim

##### Generating Censored Autoregressive Dataset with Linear Mixed Effects.

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.

##### Usage

```
ARpLMEC.sim(m, x = NULL, z = NULL, nj, beta, sigmae, D1, phi,
p.cens = 0, cens.type = "left")
```

##### Arguments

- m
Number of individuals

- x
Design matrix of the fixed effects of order

`n x s`

, corresponding to vector of fixed effects.- z
Design matrix of the random effects of order

`n x b`

, corresponding to vector of random effects.- nj
Vector

`1 x m`

with the number of observations for each subject, where`m`

is the total number of individuals.- beta
Vector of values fixed effects.

- sigmae
It's the value for sigma.

- D1
Covariance Matrix for the random effects.

- phi
Vector of length

`Arp`

, of values for autoregressive parameters.- p.cens
Censoring level for the process. Default is

`0`

- cens.type
`left`

for left censoring,`right`

for right censoring and`interval`

for interval censoring. Default is`left`

##### Value

returns list:

Vector of censoring indicators.

Vector of responses censoring.

##### References

Schumacher FL, Lachos VH, Dey DK (2017). Censored regression models with autoregressive errors: A likelihood-based perspective. Canadian Journal of Statistics. https://doi.org/10.1002/cjs.11338

Garay AM, Castro LM, Leskow J, Lachos VH (2017). Censored linear regression models for irregularly observed longitudinal data using the multivariate-t distribution. Statistical Methods in Medical Research. https://doi.org/10.1177/0962280214551191

##### Examples

```
# NOT RUN {
p.cens = 0.1
m = 50
D = matrix(c(0.049,0.001,0.001,0.002),2,2)
sigma2 = 0.30
phi = c(0.48,-0.2)
beta = c(1,2,1)
nj=rep(6,m)
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=ARpLMEC.sim(m,x,z,nj,beta,sigma2,D,phi,p.cens)
y<-data$y_cc
cc<-data$cc
# }
```

*Documentation reproduced from package ARpLMEC, version 1.0, License: GPL (>= 2)*