[A,D,CC,F,U,E] = filter(A,D,Range,...)
A
[ FAVAR ] - Estimated FAVAR object.
D
[ struct | tseries ] - Input database or tseries object with the FAVAR observables.
Range
[ numeric ] - Filter date range.
A
[ FAVAR ] - FAVAR object.
D
[ struct ] - Output database or tseries object with the FAVAR observables.
CC
[ struct | tseries ] - Re-estimated common components in the observables.
F
[ tseries ] - Re-estimated common factors.
U
[ tseries ] - Re-estimated idiosyncratic residuals.
E
[ tseries ] - Re-estimated structural residuals.
'cross='
[ true
| false
| numeric ] - Run the filter with the off-diagonal elements in the covariance matrix of idiosyncratic residuals; if false all cross-covariances are reset to zero; if a number between zero and one, all cross-covariances are multiplied by that number.
'invFunc='
[ 'auto'
| function_handle ] - Inversion method for the FMSE matrices.
'meanOnly='
[ true
| false
] - Return only mean data, i.e. point estimates.
'persist='
[ true
| false
] - If filter
or forecast
is used with 'persist='
set to true for the first time, the forecast MSE matrices and their inverses will be stored; subsequent calls of the filter
or forecast
functions will re-use these matrices until filter
or forecast
is called.
'output='
[ 'auto'
| 'dbase'
| 'tseries'
] - Format of output data.
'tolerance='
[ numeric | 0
] - Numerical tolerance under which two FMSE matrices computed in two consecutive periods will be treated as equal and their inversions will be re-used, not re-computed.
It is the user's responsibility to make sure that filter
and forecast
called with 'persist='
set to true are valid, i.e. that the previously computed FMSE matrices can be really re-used in the current run.