R6 Class Representing PriorBSVAR

The class PriorBSVARSIGN presents a prior specification for the homoskedastic bsvar model.

Public fields

p: a positive integer - the number of lags.
hyper: a (N+3)xS matrix of hyper-parameters $\mu, \delta, \lambda, \psi$.
A: a NxK normal prior mean matrix for the autoregressive parameters.
V: a KxK matrix determining the normal prior column-specific covariance for the autoregressive parameters.
S: an NxN matrix determining the inverted-Wishart prior scale of error terms covariance matrix.
nu: a positive scalar greater than N+1 - the shape of the inverted-Wishart prior for error terms covariance matrix.
data: an TxN matrix of observations.
Y: an NxT matrix of dependent variables.
X: an KxT matrix of independent variables.
Ysoc: an NxN matrix with the sum-of-coefficients dummy observations.
Xsoc: an KxN matrix with the sum-of-coefficients dummy observations.
Ysur: an NxN matrix with the single-unit-root dummy observations.
Xsur: an KxN matrix with the single-unit-root dummy observations.
mu.scale: a positive scalar - the shape of the gamma prior for $\mu$.
mu.shape: a positive scalar - the shape of the gamma prior for $\mu$.
delta.scale: a positive scalar - the shape of the gamma prior for $\delta$.
delta.shape: a positive scalar - the shape of the gamma prior for $\delta$.
lambda.scale: a positive scalar - the shape of the gamma prior for $\lambda$.
lambda.shape: a positive scalar - the shape of the gamma prior for $\lambda$.
psi.scale: a positive scalar - the shape of the inverted gamma prior for $\psi$.
psi.shape: a positive scalar - the shape of the inverted gamma prior for $\psi$.
covid: NULL or a positive integer indicating the start of the COVID-19 pandemic.

Methods

Method `new()`

Create a new prior specification PriorBSVAR.

Usage

specify_prior_bsvarSIGN$new(
  data,
  p,
  exogenous = NULL,
  stationary = rep(FALSE, ncol(data))
)

Arguments

data: the TxN data matrix of observations.
p: a positive integer - the autoregressive lag order of the SVAR model.
exogenous: a Txd matrix of exogenous variables.
stationary: an N logical vector - its element set to FALSE sets the prior mean for the autoregressive parameters of the Nth equation to the white noise process, otherwise to random walk.

Returns

A new prior specification PriorBSVARSIGN.

Examples

# a prior for 5-variable example with one lag and stationary data
data(optimism)
prior = specify_prior_bsvarSIGN$new(optimism, p = 1)
prior$B # show autoregressive prior mean

Method `get_prior()`

Returns the elements of the prior specification PriorBSVAR as a list.

Usage

specify_prior_bsvarSIGN$get_prior()

Examples

# a prior for 5-variable example with four lags
prior = specify_prior_bsvar$new(N = 5, p = 4)
prior$get_prior() # show the prior as list

Method `clone()`

The objects of this class are cloneable with this method.

Usage

specify_prior_bsvarSIGN$clone(deep = FALSE)

Arguments

deep: Whether to make a deep clone.

Examples

# a prior for 5-variable example with one lag
data(optimism)
prior = specify_prior_bsvarSIGN$new(optimism, p = 1)
prior$A  # show autoregressive prior mean
#>      [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,]    1    0    0    0    0    0
#> [2,]    0    1    0    0    0    0
#> [3,]    0    0    1    0    0    0
#> [4,]    0    0    0    1    0    0
#> [5,]    0    0    0    0    1    0


## ------------------------------------------------
## Method `specify_prior_bsvarSIGN$new`
## ------------------------------------------------

# a prior for 5-variable example with one lag and stationary data
data(optimism)
prior = specify_prior_bsvarSIGN$new(optimism, p = 1)
prior$B # show autoregressive prior mean
#> NULL


## ------------------------------------------------
## Method `specify_prior_bsvarSIGN$get_prior`
## ------------------------------------------------

# a prior for 5-variable example with four lags
prior = specify_prior_bsvar$new(N = 5, p = 4)
prior$get_prior() # show the prior as list
#> $A
#>      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14]
#> [1,]    1    0    0    0    0    0    0    0    0     0     0     0     0     0
#> [2,]    0    1    0    0    0    0    0    0    0     0     0     0     0     0
#> [3,]    0    0    1    0    0    0    0    0    0     0     0     0     0     0
#> [4,]    0    0    0    1    0    0    0    0    0     0     0     0     0     0
#> [5,]    0    0    0    0    1    0    0    0    0     0     0     0     0     0
#>      [,15] [,16] [,17] [,18] [,19] [,20] [,21]
#> [1,]     0     0     0     0     0     0     0
#> [2,]     0     0     0     0     0     0     0
#> [3,]     0     0     0     0     0     0     0
#> [4,]     0     0     0     0     0     0     0
#> [5,]     0     0     0     0     0     0     0
#> 
#> $A_V_inv
#>       [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
#>  [1,]    1    0    0    0    0    0    0    0    0     0     0     0     0
#>  [2,]    0    1    0    0    0    0    0    0    0     0     0     0     0
#>  [3,]    0    0    1    0    0    0    0    0    0     0     0     0     0
#>  [4,]    0    0    0    1    0    0    0    0    0     0     0     0     0
#>  [5,]    0    0    0    0    1    0    0    0    0     0     0     0     0
#>  [6,]    0    0    0    0    0    4    0    0    0     0     0     0     0
#>  [7,]    0    0    0    0    0    0    4    0    0     0     0     0     0
#>  [8,]    0    0    0    0    0    0    0    4    0     0     0     0     0
#>  [9,]    0    0    0    0    0    0    0    0    4     0     0     0     0
#> [10,]    0    0    0    0    0    0    0    0    0     4     0     0     0
#> [11,]    0    0    0    0    0    0    0    0    0     0     9     0     0
#> [12,]    0    0    0    0    0    0    0    0    0     0     0     9     0
#> [13,]    0    0    0    0    0    0    0    0    0     0     0     0     9
#> [14,]    0    0    0    0    0    0    0    0    0     0     0     0     0
#> [15,]    0    0    0    0    0    0    0    0    0     0     0     0     0
#> [16,]    0    0    0    0    0    0    0    0    0     0     0     0     0
#> [17,]    0    0    0    0    0    0    0    0    0     0     0     0     0
#> [18,]    0    0    0    0    0    0    0    0    0     0     0     0     0
#> [19,]    0    0    0    0    0    0    0    0    0     0     0     0     0
#> [20,]    0    0    0    0    0    0    0    0    0     0     0     0     0
#> [21,]    0    0    0    0    0    0    0    0    0     0     0     0     0
#>       [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21]
#>  [1,]     0     0     0     0     0     0     0     0
#>  [2,]     0     0     0     0     0     0     0     0
#>  [3,]     0     0     0     0     0     0     0     0
#>  [4,]     0     0     0     0     0     0     0     0
#>  [5,]     0     0     0     0     0     0     0     0
#>  [6,]     0     0     0     0     0     0     0     0
#>  [7,]     0     0     0     0     0     0     0     0
#>  [8,]     0     0     0     0     0     0     0     0
#>  [9,]     0     0     0     0     0     0     0     0
#> [10,]     0     0     0     0     0     0     0     0
#> [11,]     0     0     0     0     0     0     0     0
#> [12,]     0     0     0     0     0     0     0     0
#> [13,]     0     0     0     0     0     0     0     0
#> [14,]     9     0     0     0     0     0     0     0
#> [15,]     0     9     0     0     0     0     0     0
#> [16,]     0     0    16     0     0     0     0     0
#> [17,]     0     0     0    16     0     0     0     0
#> [18,]     0     0     0     0    16     0     0     0
#> [19,]     0     0     0     0     0    16     0     0
#> [20,]     0     0     0     0     0     0    16     0
#> [21,]     0     0     0     0     0     0     0     1
#> 
#> $B_V_inv
#>      [,1] [,2] [,3] [,4] [,5]
#> [1,]    1    0    0    0    0
#> [2,]    0    1    0    0    0
#> [3,]    0    0    1    0    0
#> [4,]    0    0    0    1    0
#> [5,]    0    0    0    0    1
#> 
#> $B_nu
#> [1] 5
#> 
#> $hyper_nu_B
#> [1] 10
#> 
#> $hyper_a_B
#> [1] 10
#> 
#> $hyper_s_BB
#> [1] 100
#> 
#> $hyper_nu_BB
#> [1] 1
#> 
#> $hyper_nu_A
#> [1] 10
#> 
#> $hyper_a_A
#> [1] 10
#> 
#> $hyper_s_AA
#> [1] 10
#> 
#> $hyper_nu_AA
#> [1] 10
#>

Public fields

Methods

Public methods

Method new()

Usage

Arguments

Returns

Examples

Method get_prior()

Usage

Examples

Method clone()

Usage

Arguments

Examples

Method `new()`

Method `get_prior()`

Method `clone()`