Filter disturbances through conditional variance model

`filter`

generalizes `simulate`

. Both function filter a series of disturbances to produce
output responses and conditional variances. However, `simulate`

autogenerates a series of mean-zero, unit-variance, independent and identically
distributed (iid) disturbances according to the distribution in the conditional variance
model object, `Mdl`

. In contrast, `filter`

lets you
directly specify your own disturbances.

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[3] Box, G. E. P., G. M. Jenkins, and G. C. Reinsel. *Time Series
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