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Generates the bootstrap-related outputs

Source: R/Bootstrap.R
Bootstrap.Rd

Generates the bootstrap-related outputs

Usage

Bootstrap(
  ModelType,
  ModelParaPE,
  NumOutPE,
  Economies,
  InputsForOutputs,
  FactorLabels,
  JLLlist,
  GVARlist,
  WishBC,
  BRWlist,
  Folder2save = NULL,
  verbose = TRUE
)

Arguments

ModelType

A character vector indicating the model type to be estimated.

ModelParaPE

A list containing the point estimates of the model parameters. For details, refer to the outputs from the Optimization function.

NumOutPE

The point estimate derived from numerical outputs. See the outputs from the NumOutputs function for further information.

Economies

A character vector containing the names of the economies included in the system.

InputsForOutputs

A list containing the necessary inputs for generating IRFs, GIRFs, FEVDs, GFEVDs and Term Premia.

FactorLabels

A list of character vectors with labels for all variables in the model.

JLLlist

List. Inputs for JLL model estimation (see JLL function). Default is NULL.

GVARlist

List. Inputs for GVAR model estimation (see GVAR function). Default is NULL.

WishBC

Whether to estimate the physical parameter model with bias correction, based on the method by Bauer, Rudebusch and Wu (2012) (see Bias_Correc_VAR function). Default is set to 0.

BRWlist

List of necessary inputs for performing the bias-corrected estimation (see Bias_Correc_VAR function).

Folder2save

Folder path where the outputs will be stored. Default option saves the outputs in a temporary directory.

verbose

Logical flag controlling function messaging. Default is TRUE.

Value

An object of class 'ATSMModelBoot' containing the following keys elements:

  • List of model parameters for each draw

  • List of numerical outputs (IRFs, GIRFs, FEVDs and GFEVDs) for each draw

  • Confidence bounds for the chosen level of significance

Available methods

- `autoplot(object, NumOutPE, type)`

Examples

# \donttest{
data("ParaSetEx")
data("InpForOutEx")
data("NumOutEx")
ModelType <- "JPS original"
Economy <- "Brazil"
FacLab <- LabFac(N = 1, DomVar = "Eco_Act", GlobalVar = "Gl_Eco_Act", Economy, ModelType)

# Adjust Forecasting setting
InpForOutEx[[ModelType]]$Bootstrap <- list(WishBootstrap = 1, methodBS = 'bs', BlockLength = 4,
                                          ndraws = 5, pctg =  95)

Boot <- Bootstrap(ModelType, ModelParaEx, NumOutEx, Economy, InpForOutEx, FacLab, JLLlist = NULL,
                 GVARlist = NULL, WishBC = 0, BRWlist = NULL, Folder2save  = NULL, verbose = TRUE)
#> 3) BOOTSTRAP ANALYSIS
#> 3.1) Estimating bootstrap setup. This may take several hours.
#> -- Done!
#> Elapsed time: 3.15 seconds
#> 3.2) Computing numerical outputs.
#> 3.3) Computing confidence bounds and producing graphical outputs.
#> Warning: cannot create dir '/tmp/RtmpqxpxJs/Outputs/JPS original/Bootstrap', reason 'No such file or directory'
#> Warning: cannot create dir '/tmp/RtmpqxpxJs/Outputs/JPS original/Bootstrap/Model Brazil', reason 'No such file or directory'
#> Desired graphs are saved in your chosen directory. Please, check: /tmp/RtmpqxpxJs 
# }