Summarises posterior draws of cumulative dynamic multipliers

Transforms posterior draws of cumulative dynamic multipliers into a table containing posterior means, medians, standard deviations, and equal-tailed credible intervals, or retains the individual draws when requested.

Usage

tidy_cdm(object, ...)

# Default S3 method
tidy_cdm(object, ...)

# S3 method for class 'PosteriorBSVAR'
tidy_cdm(
  object,
  horizon = NULL,
  probability = 0.9,
  draws = FALSE,
  model = "model1",
  scale_by = c("none", "shock_sd"),
  scale_var = NULL,
  ...
)

Arguments

object: A posterior model object or a PosteriorCDM array.
...: Additional arguments passed to computation methods.
horizon: Forecast horizon when object is a posterior model object.
probability: Probability mass of the equal-tailed credible interval.
draws: If TRUE, report individual posterior draws rather than posterior summaries.
model: Label identifying the model specification.
scale_by: Optional scaling mode for CDMs.
scale_var: Optional scaling variable specification.

Value

A bsvar_post_tbl (tibble subclass) with columns model, object_type, variable, shock, horizon, mean, median, sd, lower, and upper. When draws = TRUE, columns draw and value replace the summary statistics.

Examples

# Small posterior (S = 5 draws)
data(us_fiscal_lsuw, package = "bsvars")
spec <- bsvars::specify_bsvar$new(us_fiscal_lsuw, p = 1)
#> The identification is set to the default option of lower-triangular structural matrix.
post <- bsvars::estimate(spec, S = 5, show_progress = FALSE)

# Posterior summaries of cumulative dynamic multipliers
result <- tidy_cdm(post, horizon = 3)
head(result)
#> # A tibble: 6 × 20
#>   model  object_type variable shock horizon     mean    median      sd   lower
#>   <chr>  <chr>       <chr>    <chr>   <dbl>    <dbl>     <dbl>   <dbl>   <dbl>
#> 1 model1 cdm         ttr      ttr         0  0.0468   0.0442   0.00556  0.0425
#> 2 model1 cdm         ttr      ttr         1  0.0938   0.0852   0.0183   0.0816
#> 3 model1 cdm         ttr      ttr         2  0.140    0.123    0.0356   0.117 
#> 4 model1 cdm         ttr      ttr         3  0.184    0.159    0.0543   0.151 
#> 5 model1 cdm         ttr      gs          0  0        0        0        0     
#> 6 model1 cdm         ttr      gs          1 -0.00431 -0.000791 0.00897 -0.0165
#> # ℹ 11 more variables: upper <dbl>, analysis_type <chr>,
#> #   interval_probability <dbl>, interval_method <chr>, scale_by <chr>,
#> #   scale_var <chr>, scale_factor <dbl>, units <chr>, source_package <chr>,
#> #   source_version <chr>, n_draws <int>