[A,B,C,D,F,G,H,J,List,Nf] = system(M)
M
[ model ] - Model object whose system matrices will be returned.A
, B
, C
, D
, F
, G
, H
,J
[ numeric ] - Matrices describing the unsolved system, see Description.
List
[ cell ] - Lists of measurement variables, transition variables includint their auxiliary lags and leads, and shocks as they appear in the rows and columns of the system matrices.
Nf
[ numeric ] - Number of non-predetermined (forward-looking) transition variables (multiplied by the first Nf
columns of matrices A
and B
).
'linear='
[ @auto
| true
| false
] - Compute the model using a linear approach, i.e. differentiating around zero and not the currently assigned steady state.
'select='
[ true
| false
] - Automatically detect which equations need to be re-differentiated based on parameter changes from the last time the system matrices were calculated.
'sparse='
[ true
| false
] - Return matrices A
, B
, D
, F
, G
, and J
as sparse matrices; can be set to true
only in models with one parameterization.
The system before the model is solved has the following form:
A E[xf;xb] + B [xf(-1);xb(-1)] + C + D e = 0
F y + G xb + H + J e = 0
where E
is a conditional expectations operator, xf
is a vector of non-predetermined (forward-looking) transition variables, xb
is a vector of predetermined (backward-looking) transition variables, y
is a vector of measurement variables, and e
is a vector of transition and measurement shocks.