ARCensReg (version 3.0.1)

predict: Forecast for Autoregressive censored models with Normal and Student-t innovations

Description

Forecast from models fitted by ARCensReg and ARtCensReg.

Usage

# S3 method for ARpCRM
predict(object, x_pred, ...)
  
  # S3 method for ARtpCRM
predict(object, x_pred, ...)

Value

A time series of predictions.

Arguments

object

An object inheriting from class ARpCRM or ARtpCRM, representing a fitted AR(p) censored linear model.

x_pred

Matrix of covariates for responses to be predicted.

...

Further arguments passed to or from other methods.

Author

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

References

schumacher2017censoredARCensReg

valeriano2021censoredARCensReg

See Also

ARCensReg, ARtCensReg

Examples

# \donttest{
# Generating a sample
set.seed(2839)
n = 210
x = cbind(1, rnorm(n))
dat = rARCens(n=n, beta=c(-1,2), phi=.5, sig2=.3, x=x, cens='left', pcens=.1)

# Fitting the model
data1 = dat$data[1:205,]
fit = ARCensReg(data1$cc, data1$lcl, data1$ucl, data1$y, x[1:205,],
                 M=5, pc=.12, tol=0.001)

# Forecast
y_pred = predict(fit, x[206:n,])
mean((dat$data$y[206:n] - y_pred)^2) # MSPE# }