ARCensReg (version 3.0.2)

rARCens: Generating censored autoregressive data

Description

It simulates a censored response variable with autoregressive errors of order \(p\) following normal or Student-t innovations, with an established censoring rate.

Usage

rARCens(n, beta, phi, sig2 = 1, x = rep(1, n), cens = "left", 
  pcens = 0.1, innov = "norm", nu = NULL)

Value

data

Generated response (y), censoring indicator (cc), and lower (lcl) and upper (ucl) bounds of the interval, which contains the true value of the censored observation.

param

Theoretical parameters (beta, sig2, phi).

Arguments

n

Length of the desired time serie.

beta

Vector of theoretical regression parameters of length \(l\).

phi

Vector of theoretical autoregressive coefficients of length \(p\).

sig2

Theoretical variance of the error.

x

Matrix of covariates of dimension \(n\)x\(l\) (in models that include an intercept x should contain a column of ones).

cens

'left' for left censoring, 'right' for right censoring.

pcens

Desired censoring rate.

innov

Distribution of the innovation variable. The values are 'norm' and 't' for normal and Student-t distribution, respectively.

nu

Degrees of freedom for Student-t innovations.

Author

Fernanda L. Schumacher, Katherine L. Valeriano, Victor H. Lachos, Christian E. Galarza, and Larissa A. Matos

See Also

ARCensReg, ARtCensReg

Examples

library(ggplot2)

## Example 1: Generating a sample with normal innovations
set.seed(1234)
dat = rARCens(n=100, beta=c(1,-1), phi=c(.48,-.2), sig2=.5,
              x=cbind(1,runif(100)), cens='left', pcens=.10)

# Plotting the time serie
ggplot(data.frame(dat$data$y), aes(x=1:100, y=dat$data$y)) + geom_line() + 
  geom_line(aes(x=1:100, y=dat$data$ucl), color="red", linetype="twodash") + 
  labs(x="Time", y=bquote(y["obs"])) + theme_bw()

table(dat$data$cc)

dat$param
#[1]  1.00 -1.00  0.50  0.48 -0.20

## Example 2: Generating a sample with Student-t innovations
set.seed(8278)
dat1 = rARCens(n=100, beta=c(1,-1), phi=c(.48,-.2), sig2=.5,
               x=cbind(1,rnorm(100)), cens='right', pcens=.10, 
               innov='t', nu=3)

# Plotting the time serie
ggplot(data.frame(dat1$data$y), aes(x=1:100, y=dat1$data$y)) + geom_line() + 
  geom_line(aes(x=1:100, y=dat1$data$lcl), color="red", linetype="twodash") + 
  labs(x="Time", y=bquote(y["obs"])) + theme_bw()
  
dat1$param
#[1]  1.00 -1.00  0.50  0.48 -0.20  3.00