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R6 Class Representing StartingValuesBVARs

Source: R/specify_bvars.R
specify_starting_values_bvars.Rd

The class StartingValuesBVARs presents starting values for the Bayesian hierarchical panel VAR model.

Public fields

A_c

an KxNxC array of starting values for the local parameter \(\mathbf{A}_c\).

Sigma_c

an NxNxC array of starting values for the local parameter \(\mathbf{\Sigma}_c\).

nu

a C-vector of positive starting values for the parameter \(\nu\).

m

a C-vector of starting values for the parameter \(m\).

w

a C-vector of positive starting values for the parameter \(w\).

s

a C-vector of positive starting values for the parameter \(s\).

Methods

Public methods

Method new()

Create new starting values StartingValuesBVARs

Usage

specify_starting_values_bvars$new(C, N, p, d = 0)

Arguments

C

a positive integer - the number of countries in the data.

N

a positive integer - the number of dependent variables in the model.

p

a positive integer - the autoregressive lag order of the SVAR model.

d

a positive integer - the number of exogenous variables in the model.

Returns

Starting values StartingValuesBVARs

Examples

# starting values for Bayesian VARs 2-country model with 4 lags for a 3-variable system.
sv = specify_starting_values_bvars$new(C = 2, N = 3, p = 4)

Method get_starting_values()

Returns the elements of the starting values StartingValuesBVARs as a list.

Usage

specify_starting_values_bvars$get_starting_values()

Examples

# starting values for bvars with 1 lag for a 3-variable system
sv = specify_starting_values_bvars$new(C = 2, N = 3, p = 1)
sv$get_starting_values()   # show starting values as list

Method set_starting_values()

Returns the elements of the starting values StartingValuesBVARs as a list.

Usage

specify_starting_values_bvars$set_starting_values(last_draw)

Arguments

last_draw

a list containing the same elements as object StartingValuesBVARs.

Returns

An object of class StartingValuesBVARs including the last draw of the current MCMC as the starting value to be passed to the continuation of the MCMC estimation.

Examples

sv = specify_starting_values_bvars$new(C = 2, N = 3, p = 1)

# Modify the starting values by:
sv_list = sv$get_starting_values()   # getting them as list
sv_list$A <- matrix(rnorm(12), 3, 4) # modifying the entry
sv$set_starting_values(sv_list)      # providing to the class object

Method clone()

The objects of this class are cloneable with this method.

Usage

specify_starting_values_bvars$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

# starting values for a Bayesian Panel VAR
sv = specify_starting_values_bvars$new(C = 2, N = 3, p = 1)


## ------------------------------------------------
## Method `specify_starting_values_bvars$new`
## ------------------------------------------------

# starting values for Bayesian VARs 2-country model with 4 lags for a 3-variable system.
sv = specify_starting_values_bvars$new(C = 2, N = 3, p = 4)


## ------------------------------------------------
## Method `specify_starting_values_bvars$get_starting_values`
## ------------------------------------------------

# starting values for bvars with 1 lag for a 3-variable system
sv = specify_starting_values_bvars$new(C = 2, N = 3, p = 1)
sv$get_starting_values()   # show starting values as list
#> $A_c
#> , , 1
#> 
#>               [,1]          [,2]          [,3]
#> [1,]  0.0009264790  0.0004239207 -0.0010126058
#> [2,]  0.0006523921 -0.0000440565  0.0002226111
#> [3,]  0.0004231408  0.0008209945 -0.0010010239
#> [4,] -0.0008625480 -0.0003605169  0.0003202384
#> 
#> , , 2
#> 
#>               [,1]          [,2]          [,3]
#> [1,] -0.0009029412 -0.0002930912 -0.0013827853
#> [2,]  0.0009080859  0.0002653011  0.0002053105
#> [3,] -0.0003150738 -0.0019554789  0.0004125065
#> [4,]  0.0015206106 -0.0007476931  0.0007379095
#> 
#> 
#> $Sigma_c
#> , , 1
#> 
#>           [,1]      [,2]      [,3]
#> [1,]  4.518844 -2.748561  2.616351
#> [2,] -2.748561  2.697226 -1.434866
#> [3,]  2.616351 -1.434866  4.323841
#> 
#> , , 2
#> 
#>            [,1]      [,2]       [,3]
#> [1,]  2.5354358 -1.045453  0.1227443
#> [2,] -1.0454531 13.291854 -2.2304913
#> [3,]  0.1227443 -2.230491  1.9353094
#> 
#> 
#> $nu
#> [1] 4.1 4.1
#> 
#> $m
#> [1] 0.0018590713 0.0001393031
#> 
#> $w
#> [1] 0.08409662 0.14187185
#> 
#> $s
#> [1] 0.4747519 0.8827887
#> 


## ------------------------------------------------
## Method `specify_starting_values_bvars$set_starting_values`
## ------------------------------------------------

sv = specify_starting_values_bvars$new(C = 2, N = 3, p = 1)

# Modify the starting values by:
sv_list = sv$get_starting_values()   # getting them as list
sv_list$A <- matrix(rnorm(12), 3, 4) # modifying the entry
sv$set_starting_values(sv_list)      # providing to the class object