Joint prior

Defines the joint prior of a structural block.

Usage

joint_prior(
  block,
  var.index = 1:block$n,
  a1 = block$a1[var.index],
  R1 = block$R1[var.index, var.index]
)

Arguments

block

dlm_block object: The structural block.

var.index

Integer: The index of the variables from which to set the prior.

a1

Numeric: The prior mean.

R1

Matrix: The prior covariance matrix.

Value

A dlm_block object with the desired prior.

Details

The discount factor must be the same for all variables whose prior is being modified. For the details about the implementation see dos Santos et al. (2024) .

References

Junior, Silvaneo Vieira dos Santos, Mariane Branco Alves, Helio S. Migon (2024). “kDGLM: an R package for Bayesian analysis of Dynamic Generialized Linear Models.”

See also

Other auxiliary functions for defining priors.: CAR_prior(), zero_sum_prior()

Examples

polynomial_block(mu = 1, D = 0.95) |>
  block_mult(5) |>
  joint_prior(var.index = 1:2, R1 = matrix(c(1, 0.5, 0.5, 1), 2, 2))
#> Mixed DLM block.
#> latent states: 
#>     Var.Poly.1: Level (1 variable(s))
#>     Var.Poly.2: Level (1 variable(s))
#>     Var.Poly.3: Level (1 variable(s))
#>     Var.Poly.4: Level (1 variable(s))
#>     Var.Poly.5: Level (1 variable(s))
#> 
#> Linear predictors: 
#>     mu.1
#>     mu.2
#>     mu.3
#>     mu.4
#>     mu.5
#> 
#> Status: defined
#> Serie length: 1
#> Interventions at: 
#> Number of latent states: 5
#> Number of linear predictors: 5