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Generate univariate autoregressive integrated moving average (ARIMA) model impulse response function (IRF)

`impulse`

generates, or plots, the impulse response function (IRF) of a univariate autoregressive integrated moving average (ARIMA) process specified by an `arima`

model object.

Alternatively, you can use `armairf`

to generate or plot the IRF of an ARMA process specified by AR and MA lag operator polynomial coefficients.

To improve performance of the filtering algorithm, specify the number of periods to include in the IRF

`numObs`

. When you do not specify`numObs`

,`impulse`

computes the IRF by using the lag operator polynomial division algorithm, which is relatively slow, to represent the input model`Mdl`

as a truncated, infinite-degree, moving average model. The length of the resulting IRF is generally unknown.

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

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

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

[4] Lütkepohl, Helmut. *New Introduction to Multiple Time Series Analysis*. New York, NY: Springer-Verlag, 2007.

[5] Wold, H. *A Study in the Analysis of Stationary Time Series*. Uppsala, Sweden: Almqvist & Wiksell, 1938.