Description Usage Arguments Value Examples
Given a sparse-spline representation of the observation equation, this function performs filtering to derive the conditional distributions of the filtered (x_{t|t}) and predicted (x_{t|t-1}) hidden states.
1 | lgf1(Y, out.spam, Tt, HHinv, GGt, x0, P0)
|
Y |
the observed data, a Nxd matrix |
out.spam |
the sparse additive spline model associated with the observation equation, as produced by |
Tt |
the state transition matrix, pxp |
HHinv |
the inverse of the observation noise variance matrix |
GGt |
the transition noise variance matris |
x0 |
prior mean of the state variables |
P0 |
prior variance of the state variables |
A list with components xt
and xtt
, the predicted and filtered state means respectively and Pt
and Ptt
, the associated variances.
1 2 3 4 5 6 |
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