# Residuals of a fitted carx object

### Description

Computes the residuals of fitted carx object. When no censoring is present, the ordinary residuals will be computed. Otherwise, the simulated residuals (Gourieroux, Monfort, Renault, and Trognon 1987) of a fitted carx object will be computed, as suggested in Wang and Chan (2015).

### Usage

 1 2 3 ## S3 method for class 'carx' residuals(object, type = c("raw", "pearson"), seed = NULL, ...) 

### Arguments

 object a fitted carx object. type a string indicates which type of residual is to be returned. "raw" returns the (simulated) residuals; "pearson" returns the raw residuals divided by estimated standard error of the residuals. seed the seed for the random number generator. ... not used.

### Details

The simulated residuals are constructed as follows. First, impute each unobserved Y_t^* by a (random) realization from the conditional distribution D(Y_t^*|\{(Y_s,X_s)\}_{s=1}^t), evaluated at the parameter estimate. Then, refit the model with (Y_t^* , X_t) so obtained, via the method of conditional maximum likelihood; the residuals from the latter model are the simulated residuals \varepsilon_t.

### Value

the simulated residuals.

### References

Gourieroux C, Monfort A, Renault E, Trognon A (1987). "Simulated residuals." Journal of Econometrics, 34(1), 201-252.

Wang C, Chan KS (2015). "Quasi-likelihood estimation of a censored autoregressive model with exogenous variables." Submitted.

### Examples

 1 2 3 4 5 6 dat = carxSim(nObs=100,seed=0) mdl <- carx(y~X1+X2-1,data=dat, p=2, CI.compute = FALSE) #compute the raw residuals res = residuals(mdl,type="raw") #compute the Pearson residuals res = residuals(mdl,type="pearson") 

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