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**Class: **regARIMA

Infer innovations of regression models with ARIMA errors

`E = infer(Mdl,Y)`

[E,U,V,logL]
= infer(Mdl,Y)

[E,U,V,logL]
= infer(Mdl,Y,Name,Value)

infers
residuals of a univariate regression model with ARIMA time series
errors fit to response data `E`

= infer(`Mdl`

,`Y`

)`Y`

.

`[`

additionally
returns the unconditional disturbances `E`

,`U`

,`V`

,`logL`

]
= infer(`Mdl`

,`Y`

)`U`

, the innovation
variances `V`

, and the loglikelihood objective function
values `logL`

.

`[`

returns
the output arguments using additional options specified by one or
more `E`

,`U`

,`V`

,`logL`

]
= infer(`Mdl`

,`Y`

,`Name,Value`

)`Name,Value`

pair arguments.

[1] Box, G. E. P., G. M. Jenkins, and G. C. Reinsel. *Time
Series Analysis: Forecasting and Control*. 3rd ed. Englewood
Cliffs, NJ: Prentice Hall, 1994.

[2] Davidson, R., and J. G. MacKinnon. *Econometric
Theory and Methods*. Oxford, UK: Oxford University Press,
2004.

[3] Enders, W. *Applied Econometric Time Series*.
Hoboken, NJ: John Wiley & Sons, Inc., 1995.

[4] Hamilton, J. D. *Time Series Analysis*.
Princeton, NJ: Princeton University Press, 1994.

[5] Pankratz, A. *Forecasting with Dynamic Regression
Models.* John Wiley & Sons, Inc., 1991.

[6] Tsay, R. S. *Analysis of Financial Time Series*.
2nd ed. Hoboken, NJ: John Wiley & Sons, Inc., 2005.

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