carxSim: Simulate data from a 'carx' model
In carx: Censored Autoregressive Model with Exogenous Covariates

Description Usage Arguments Value References See Also Examples

Use the provided parameters in the supplied carx model and other settings to simulate data from the carx model; see Wang and Chan (2017).

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carxSim(nObs = 200, prmtrAR = c(-0.28, 0.25), prmtrX = c(0.2, 0.4),
  sigma = 0.6, lcl = -1, ucl = 1, x = NULL, seed = NULL,
  inno.dist = c("normal", "t"), t.df = 5, intercept = 0)

`nObs`	number of observations to be simulated.
`prmtrAR`	the AR parameter.
`prmtrX`	the regression parameters for X.
`sigma`	the innovation standard deviation for the AR process.
`lcl`	the lower censoring limit.
`ucl`	the upper censoring limit.
`x`	optional matrix for X. Default = `NULL`, in which case X will be simulated from the standard normal distribution with dimensions determined by `nObs` and `prmtrX`.
`seed`	optional to set the seed of random number generator used by `R`, default=`NULL`.
`inno.dist`	innovation distribution, can be "normal" or "t", default="normal". If it is "t", its degree of freedom should be supplied in `t.df`.
`t.df`	the degree of freedom of the t distribution, used only if `inno.dist`="t". Default=5.
`intercept`	the intercept in the regression. Default=0.

a data frame of simulated y, x, ci, lcl and ucl.

Wang C, Chan KS (2017). "Quasi-likelihood estimation of a censored autoregressive model with exogenous variables." Journal of the American Statistical Association. 2017 Mar 20(just-accepted). with exogenous variables." Submitted.

carx for model specification.