get_B_yt {sstvars} | R Documentation |
Compute the impact matrix B_{y,t}
for a single time period
Description
get_B_yt
computes the impact matrix B_{y,t}
. For "ind_Student"
and "ind_skewed_t"
models
B_{y,t}=\sum_{m=1}^M\alpha_{m,t}B_m
. For models identified by heteroskedasticity B_{y,t}=W\sqrt{\sum_{m=1}^M\alpha_{m,t}\Lambda_m}
.
For recursive identification B_{y,t}
is obtained from the Cholesky decomposition of the conditional covariance matrix.
Usage
get_B_yt(
all_Omegas,
alpha_mt,
W,
lambdas,
cond_dist = c("Gaussian", "Student", "ind_Student", "ind_skewed_t"),
identification = c("reduced_form", "recursive", "non-Gaussianity",
"heteroskedasticity")
)
Arguments
all_Omegas |
a 3D array such that the covariance matrix (or impact matrix |
alpha_mt |
an |
W |
a |
lambdas |
a |
cond_dist |
specifies the conditional distribution of the model as |
identification |
is it reduced form model or an identified structural model; if the latter, how is it identified (see the vignette or the references for details)?
|
Details
This is used in simulation of the counterfactual scenarios.
Value
Returns the (d \times d)
impact matrix for the time period t
.