summary.PosteriorBSVARMSH: Provides posterior summary of heteroskedastic Structural VAR...

In bsvars: Bayesian Estimation of Structural Vector Autoregressive Models

Provides posterior summary of heteroskedastic Structural VAR estimation

Description

Provides posterior mean, standard deviations, as well as 5 and 95 percentiles of the parameters: the structural matrix B, autoregressive parameters A, and hyper parameters.

Usage

## S3 method for class 'PosteriorBSVARMSH'
summary(object, ...)

Arguments

object	an object of class PosteriorBSVARMSH obtained using the estimate() function applied to heteroskedastic Bayesian Structural VAR model specification set by function specify_bsvar_msh$new() containing draws from the posterior distribution of the parameters.
...	additional arguments affecting the summary produced.

Value

A list reporting the posterior mean, standard deviations, as well as 5 and 95 percentiles of the parameters: the structural matrix B, autoregressive parameters A, and hyper-parameters.

Author(s)

Tomasz Woźniak [e-mail]

See Also

estimate, specify_bsvar_msh

Examples

# upload data
data(us_fiscal_lsuw)

# specify the model and set seed
set.seed(123)
specification  = specify_bsvar_msh$new(us_fiscal_lsuw)

# run the burn-in
burn_in        = estimate(specification, 10)

# estimate the model
posterior      = estimate(burn_in, 20)
summary(posterior)

# workflow with the pipe |>
############################################################
set.seed(123)
us_fiscal_lsuw |>
  specify_bsvar_msh$new() |>
  estimate(S = 10) |> 
  estimate(S = 20) |> 
  summary()

bsvars documentation built on Oct. 24, 2024, 5:11 p.m.