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R6 Class Representing StartingValuesBVARPANEL

Source: R/specify_bvarpanel.R
specify_starting_values_bvarPANEL.Rd

The class StartingValuesBVARPANEL 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 \(\mathbf{\Sigma}_c\).

A

an KxN matrix of starting values for the global parameter \(\mathbf{A}\).

V

an KxK matrix of starting values for the global parameter \(\mathbf{V}\).

Sigma

an NxN matrix of starting values for the global parameter \(\mathbf{\Sigma}\).

nu

a positive scalar with starting values for the global parameter \(\nu\).

m

a positive scalar with starting values for the global hyper-parameter \(m\).

w

a positive scalar with starting values for the global hyper-parameter \(w\).

s

a positive scalar with starting values for the global hyper-parameter \(s\).

Methods

Public methods

Method new()

Create new starting values StartingValuesBVARPANEL

Usage

specify_starting_values_bvarPANEL$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 StartingValuesBVARPANEL

Examples

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

Method get_starting_values()

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

Usage

specify_starting_values_bvarPANEL$get_starting_values()

Examples

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

Method set_starting_values()

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

Usage

specify_starting_values_bvarPANEL$set_starting_values(last_draw)

Arguments

last_draw

a list containing the same elements as object StartingValuesBVARPANEL.

Returns

An object of class StartingValuesBVARPANEL 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_bvarPANEL$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_bvarPANEL$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

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


## ------------------------------------------------
## Method `specify_starting_values_bvarPANEL$new`
## ------------------------------------------------

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


## ------------------------------------------------
## Method `specify_starting_values_bvarPANEL$get_starting_values`
## ------------------------------------------------

# starting values for a homoskedastic bsvar with 1 lag for a 3-variable system
sv = specify_starting_values_bvarPANEL$new(C = 2, N = 3, p = 1)
sv$get_starting_values()   # show starting values as list
#> $A_c
#> , , 1
#> 
#>              [,1]          [,2]          [,3]
#> [1,] 0.0004938469 -0.0015372338  0.0007334974
#> [2,] 0.0004547900  0.0012301562 -0.0007353337
#> [3,] 0.0014632086  0.0005701989  0.0014122754
#> [4,] 0.0004796409 -0.0003327847 -0.0009386183
#> 
#> , , 2
#> 
#>               [,1]          [,2]          [,3]
#> [1,]  1.014699e-03  0.0009797475 -0.0018580369
#> [2,] -2.469808e-03 -0.0014002001  0.0007901463
#> [3,]  8.508482e-04  0.0003807436 -0.0004428356
#> [4,]  9.455169e-05 -0.0011507121  0.0021748359
#> 
#> 
#> $Sigma_c
#> , , 1
#> 
#>           [,1]     [,2]      [,3]
#> [1,] 6.6393563 1.961107 0.3196957
#> [2,] 1.9611066 1.769698 0.9090700
#> [3,] 0.3196957 0.909070 1.6013052
#> 
#> , , 2
#> 
#>          [,1]      [,2]      [,3]
#> [1,] 1.997355  1.316814  1.063608
#> [2,] 1.316814  3.805323 -2.797677
#> [3,] 1.063608 -2.797677  5.458455
#> 
#> 
#> $A
#>              [,1]         [,2]          [,3]
#> [1,] 1.000388e+00  0.001155433 -0.0018856120
#> [2,] 1.095711e-03  0.999928285 -0.0001751325
#> [3,] 3.220973e-05 -0.002349186  0.9992730073
#> [4,] 5.571354e-04  0.001599875  0.0004539026
#> 
#> $V
#>            [,1]       [,2]       [,3]       [,4]
#> [1,]  0.7069639 -0.9336635 -0.1640911  0.2395434
#> [2,] -0.9336635  5.7053972  3.0942149 -1.7204673
#> [3,] -0.1640911  3.0942149 10.3761879 -2.2072563
#> [4,]  0.2395434 -1.7204673 -2.2072563  1.3257008
#> 
#> $Sigma
#>             [,1]      [,2]        [,3]
#> [1,]  2.07804577 0.3351448 -0.07095534
#> [2,]  0.33514484 2.0530515  1.85028610
#> [3,] -0.07095534 1.8502861  2.10424678
#> 
#> $nu
#> [1] 4.1
#> 
#> $m
#> [1] 0.0006332046
#> 
#> $w
#> [1] 2.309897
#> 
#> $s
#> [1] 0.7855444
#> 


## ------------------------------------------------
## Method `specify_starting_values_bvarPANEL$set_starting_values`
## ------------------------------------------------

sv = specify_starting_values_bvarPANEL$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