BVAR (version 0.1.5)

bv_mn: Minnesota prior settings

Description

Provide settings for the Minnesota prior to bv_priors.

Usage

bv_mn(lambda = bv_lambda(0.2, 0.4, 0.0001, 5), alpha = bv_alpha(2,
  0.25, 1, 3), psi = bv_psi(0.004, 0.004, "auto"), var = 10000000,
  b = "auto")
bv_lambda(mode = 0.2, sd = 0.4, min = 0.0001, max = 5)
bv_alpha(mode = 2, sd = 0.25, min = 1, max = 3)
bv_psi(scale = 0.004, shape = 0.004, mode = "auto", min = "auto",
  max = "auto")

Arguments

lambda

List constructed via bv_lambda. Possible parameters are mode, sd, min and max.

alpha

List constructed via bv_alpha. Possible parameters are mode, min and max. High values for mode may affect invertibility of the augmented data matrix.

psi

Named list with elements scale, shape and mode. Length needs to match the number of variables (i.e. columns) in the data. By default parameters are set automatically as the squareroot of the innovations variance after fitting an \(AR(p)\) model to the data.

var

Numeric scalar with the prior variance on the model's constant.

b

Numeric matrix with the prior mean.

mode

Numeric scalar (/vector). Mode (or the like) of the parameter.

sd

Numeric scalar with the standard deviation.

min

Numeric scalar (/vector). Minimum allowed value.

max

Numeric scalar (/vector). Maximum allowed value.

scale, shape

Numeric scalar. Scale and shape parameters of the Gamma distribution.

Value

Returns a named list of class bv_minnesota with options for bvar.

Examples

# NOT RUN {
# Adjust alpha fully and the prior variance.
bv_mn(
  alpha = bv_alpha(mode = 0.5, sd = 1, min = 1e-12, max = 10),
  var = 1e6
)

# Only adjust lambda's standard deviation
bv_mn(
  lambda = bv_lambda(sd = 2)
)
# }