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Smoothed inference of operative latent states in Markov-switching dynamic regression data

uses additional
options specified by one or more name-value pair arguments. For example, `SS`

= smooth(`Mdl`

,`Y`

,`Name,Value`

)`'Y0',Y0`

initializes the dynamic component of each submodel by using the presample response data `Y0`

.

`smooth`

refines current estimates of the state distribution that `filter`

produces by iterating backward from the full sample history `Y`

.

[1]
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[2]
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[3]
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[4]
Hamilton, James D. *Time Series Analysis*. Princeton, NJ: Princeton University Press, 1994.

[5]
Kim, C.-J. "Dynamic Linear Models with Markov Switching." *Journal of Econometrics*. Vol. 60, 1994, pp. 1–22.