Duration summaries for posterior IRFs and CDMs — duration

Summarise how long a response satisfies a threshold condition over the available horizons.

Usage

duration_response(object, ...)

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

# S3 method for class 'PosteriorIR'
duration_response(
  object,
  variables = NULL,
  shocks = NULL,
  variable = NULL,
  shock = NULL,
  relation = c(">", ">=", "<", "<="),
  value = 0,
  absolute = FALSE,
  mode = c("consecutive", "total"),
  probability = 0.9,
  model = "model1",
  ...
)

# S3 method for class 'PosteriorBSVAR'
duration_response(
  object,
  horizon = NULL,
  type = c("irf", "cdm"),
  variables = NULL,
  shocks = NULL,
  variable = NULL,
  shock = NULL,
  relation = c(">", ">=", "<", "<="),
  value = 0,
  absolute = FALSE,
  mode = c("consecutive", "total"),
  probability = 0.9,
  model = "model1",
  scale_by = c("none", "shock_sd"),
  scale_var = NULL,
  ...
)

# S3 method for class 'PosteriorBSVARMIX'
duration_response(
  object,
  horizon = NULL,
  type = c("irf", "cdm"),
  variables = NULL,
  shocks = NULL,
  variable = NULL,
  shock = NULL,
  relation = c(">", ">=", "<", "<="),
  value = 0,
  absolute = FALSE,
  mode = c("consecutive", "total"),
  probability = 0.9,
  model = "model1",
  scale_by = c("none", "shock_sd"),
  scale_var = NULL,
  ...
)

# S3 method for class 'PosteriorBSVARMSH'
duration_response(
  object,
  horizon = NULL,
  type = c("irf", "cdm"),
  variables = NULL,
  shocks = NULL,
  variable = NULL,
  shock = NULL,
  relation = c(">", ">=", "<", "<="),
  value = 0,
  absolute = FALSE,
  mode = c("consecutive", "total"),
  probability = 0.9,
  model = "model1",
  scale_by = c("none", "shock_sd"),
  scale_var = NULL,
  ...
)

# S3 method for class 'PosteriorBSVARSV'
duration_response(
  object,
  horizon = NULL,
  type = c("irf", "cdm"),
  variables = NULL,
  shocks = NULL,
  variable = NULL,
  shock = NULL,
  relation = c(">", ">=", "<", "<="),
  value = 0,
  absolute = FALSE,
  mode = c("consecutive", "total"),
  probability = 0.9,
  model = "model1",
  scale_by = c("none", "shock_sd"),
  scale_var = NULL,
  ...
)

# S3 method for class 'PosteriorBSVART'
duration_response(
  object,
  horizon = NULL,
  type = c("irf", "cdm"),
  variables = NULL,
  shocks = NULL,
  variable = NULL,
  shock = NULL,
  relation = c(">", ">=", "<", "<="),
  value = 0,
  absolute = FALSE,
  mode = c("consecutive", "total"),
  probability = 0.9,
  model = "model1",
  scale_by = c("none", "shock_sd"),
  scale_var = NULL,
  ...
)

# S3 method for class 'PosteriorBSVARSIGN'
duration_response(
  object,
  horizon = NULL,
  type = c("irf", "cdm"),
  variables = NULL,
  shocks = NULL,
  variable = NULL,
  shock = NULL,
  relation = c(">", ">=", "<", "<="),
  value = 0,
  absolute = FALSE,
  mode = c("consecutive", "total"),
  probability = 0.9,
  model = "model1",
  scale_by = c("none", "shock_sd"),
  scale_var = NULL,
  ...
)

# S3 method for class 'PosteriorCDM'
duration_response(
  object,
  variables = NULL,
  shocks = NULL,
  variable = NULL,
  shock = NULL,
  relation = c(">", ">=", "<", "<="),
  value = 0,
  absolute = FALSE,
  mode = c("consecutive", "total"),
  probability = 0.9,
  model = "model1",
  ...
)

Arguments

object: A posterior model object, PosteriorIR, or PosteriorCDM.
...: Additional arguments passed to computation methods.
variables: Optional response-variable subset (character or integer vector).
shocks: Optional shock subset (character or integer vector).
variable: Deprecated. Use variables instead.
shock: Deprecated. Use shocks instead.
relation: Comparison operator.
value: Threshold value.
absolute: If TRUE, search for the largest absolute response.
mode: Either "consecutive" for the duration until first violation or "total" for the total count of satisfying horizons.
probability: Equal-tailed interval probability.
model: Optional model identifier.
horizon: Maximum horizon used when object is a posterior model object.
type: Response type for posterior model objects: "irf" or "cdm".
scale_by: Optional scaling mode for CDMs.
scale_var: Optional scaling variable specification.

Value

A bsvar_post_tbl with columns model, object_type, variable, shock, relation, threshold, mode, mean_duration, median_duration, sd_duration, lower_duration, and upper_duration.

Examples

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)

dur <- duration_response(post, horizon = 3, relation = ">", value = 0)
print(dur)
#> # A tibble: 9 × 12
#>   model  object_type  variable shock relation threshold mode       mean_duration
#>   <chr>  <chr>        <chr>    <chr> <chr>        <dbl> <chr>              <dbl>
#> 1 model1 duration_irf ttr      ttr   >                0 consecuti…           4  
#> 2 model1 duration_irf ttr      gs    >                0 consecuti…           0  
#> 3 model1 duration_irf ttr      gdp   >                0 consecuti…           0  
#> 4 model1 duration_irf gs       ttr   >                0 consecuti…           2.2
#> 5 model1 duration_irf gs       gs    >                0 consecuti…           4  
#> 6 model1 duration_irf gs       gdp   >                0 consecuti…           0  
#> 7 model1 duration_irf gdp      ttr   >                0 consecuti…           2.6
#> 8 model1 duration_irf gdp      gs    >                0 consecuti…           2.6
#> 9 model1 duration_irf gdp      gdp   >                0 consecuti…           4  
#> # ℹ 4 more variables: median_duration <dbl>, sd_duration <dbl>,
#> #   lower_duration <dbl>, upper_duration <dbl>