{
  "_id": "6a27cc2924555f66ed543807",
  "Package": "bsvars",
  "Type": "Package",
  "Title": "Bayesian Estimation of Structural Vector Autoregressive Models",
  "Description": "Provides fast and efficient procedures for Bayesian\nanalysis of Structural Vector Autoregressions. This package\nestimates a wide range of models, including homo-,\nheteroskedastic, and non-normal specifications. Structural\nmodels can be identified by adjustable exclusion restrictions,\ntime-varying volatility, or non-normality, and include\nexclusion restrictions on autoregressive parameters. They all\ninclude a flexible three-level equation-specific local-global\nhierarchical prior distribution for the estimated level of\nshrinkage for autoregressive and structural parameters.\nAdditionally, the package facilitates predictive and structural\nanalyses such as impulse responses, forecast error variance and\nhistorical decompositions, forecasting, verification of\nheteroskedasticity, non-normality, and hypotheses on\nautoregressive parameters, as well as analyses of structural\nshocks, volatilities, and fitted values. Beautiful plots,\ninformative summary functions, and extensive documentation\nincluding the vignette by Woźniak (2025)\n<doi:10.48550/arXiv.2410.15090> complement all this. The\nimplemented techniques align closely with those presented in\nLütkepohl, Shang, Uzeda, & Woźniak (2025)\n<doi:10.1016/j.jeconom.2025.106107>, Lütkepohl & Woźniak (2020)\n<doi:10.1016/j.jedc.2020.103862>, and Song & Woźniak (2021)\n<doi:10.1093/acrefore/9780190625979.013.174>. The 'bsvars'\npackage is aligned regarding objects, workflows, and code\nstructure with the R package 'bsvarSIGNs' by Wang & Woźniak\n(2024) <doi:10.32614/CRAN.package.bsvarSIGNs>, and they\nconstitute an integrated toolset.",
  "Version": "4.0",
  "Date": "2025-04-16",
  "Authors@R": "c(person(\ngiven = \"Tomasz\",\nfamily = \"Woźniak\",\nemail = \"wozniak.tom@pm.me\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-2212-2378\")\n),\nperson(\ngiven = \"Xiaolei\",\nfamily = \"Wang\",\nemail = \"adamwang15@gmail.com\",\nrole = c(\"ctb\"),\ncomment = c(ORCID = \"0009-0005-6192-9061\", \"corrected C++ code for historical decompositions\")\n),\nperson(\ngiven = \"Bruno\",\nfamily =\"Cavalcante\",\nemail = \"bruno.cavalcante@fgv.edu.br\",\nrole = c(\"ctb\"),\ncomment = c(ORCID = \"0009-0005-7252-7658\", \"corrected R code for HMSH forecasting\")\n)\n)",
  "Maintainer": "Tomasz Woźniak <wozniak.tom@pm.me>",
  "License": "GPL (>= 3)",
  "URL": "https://bsvars.org/bsvars/",
  "BugReports": "https://github.com/bsvars/bsvars/issues",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "VignetteBuilder": "knitr",
  "RoxygenNote": "7.3.3",
  "Repository": "https://bsvars.r-universe.dev",
  "Date/Publication": "2026-06-09 07:03:28 UTC",
  "RemoteUrl": "https://github.com/bsvars/bsvars",
  "RemoteRef": "HEAD",
  "RemoteSha": "2c0a8cebdb94c18bacf0467a5e50a7290796eab7",
  "NeedsCompilation": "yes",
  "Packaged": {
    "Date": "2026-06-09 08:01:24 UTC",
    "User": "root"
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  "Author": "Tomasz Woźniak [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-2212-2378>),\nXiaolei Wang [ctb] (ORCID: <https://orcid.org/0009-0005-6192-9061>,\ncorrected C++ code for historical decompositions),\nBruno Cavalcante [ctb] (ORCID: <https://orcid.org/0009-0005-7252-7658>,\ncorrected R code for HMSH forecasting)",
  "MD5sum": "2c916ca0c12ccb70d64fc848cba8a10c",
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  "_created": "2026-06-09T08:01:24.000Z",
  "_published": "2026-06-09T08:17:45.660Z",
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  "_buildurl": "https://github.com/r-universe/bsvars/actions/runs/27192191022",
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  "_commit": {
    "id": "2c0a8cebdb94c18bacf0467a5e50a7290796eab7",
    "author": "Tomasz Woźniak <wozniak.tom@pm.me>",
    "committer": "Tomasz Woźniak <wozniak.tom@pm.me>",
    "message": "#137 lsuw data update\n",
    "time": 1780988608
  },
  "_maintainer": {
    "name": "Tomasz Woźniak",
    "email": "wozniak.tom@pm.me",
    "login": "donotdespair",
    "mastodon": "@tomaszwozniak@fosstodon.org",
    "bluesky": "@tomaszwozniak.bsky.social",
    "linkedin": "in/tomaszwwozniak",
    "orcid": "0000-0003-2212-2378",
    "description": "A Bayesian econometrician developing methods for empirical macro analyses and programming in R and cpp. Author of R packages bsvars.org",
    "uuid": 78328370
  },
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  "_owner": "bsvars",
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  "_usedby": 3,
  "_updates": [
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  ],
  "_tags": [],
  "_topics": [
    "bayesian-inference",
    "econometrics",
    "vector-autoregression",
    "openblas",
    "cpp",
    "openmp"
  ],
  "_stars": 62,
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    "name": "bsvars",
    "description": "We develop R packages for Bayesian Structural Vector Autoregressions using frontier econometric methods and compiled code written in cpp"
  },
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    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/bsvars"
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  "_devurl": "https://github.com/bsvars/bsvars",
  "_pkgdown": "https://bsvars.org/bsvars/",
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  "_rbuild": "4.6.0",
  "_assets": [
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    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/readme.html",
    "extra/readme.md",
    "manual.pdf"
  ],
  "_homeurl": "https://github.com/bsvars/bsvars",
  "_realowner": "bsvars",
  "_cranurl": true,
  "_releases": [
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      "date": "2022-09-01"
    },
    {
      "version": "2.0.0",
      "date": "2023-10-24"
    },
    {
      "version": "2.1.0",
      "date": "2023-12-11"
    },
    {
      "version": "3.0",
      "date": "2024-06-19"
    },
    {
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      "date": "2024-06-28"
    },
    {
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      "date": "2024-07-14"
    },
    {
      "version": "3.2",
      "date": "2024-10-24"
    }
  ],
  "_exports": [
    "compute_conditional_sd",
    "compute_fitted_values",
    "compute_historical_decompositions",
    "compute_impulse_responses",
    "compute_regime_probabilities",
    "compute_structural_shocks",
    "compute_variance_decompositions",
    "estimate",
    "forecast",
    "normalise",
    "plot_ribbon",
    "specify_bsvar",
    "specify_bsvar_exh",
    "specify_bsvar_hmsh",
    "specify_bsvar_mix",
    "specify_bsvar_msh",
    "specify_bsvar_sv",
    "specify_bsvar_t",
    "specify_data_matrices",
    "specify_identification_bsvars",
    "specify_posterior_bsvar",
    "specify_posterior_bsvar_exh",
    "specify_posterior_bsvar_hmsh",
    "specify_posterior_bsvar_mix",
    "specify_posterior_bsvar_msh",
    "specify_posterior_bsvar_sv",
    "specify_posterior_bsvar_t",
    "specify_prior_bsvar",
    "specify_prior_bsvar_exh",
    "specify_prior_bsvar_mix",
    "specify_prior_bsvar_msh",
    "specify_prior_bsvar_sv",
    "specify_prior_bsvar_t",
    "specify_starting_values_bsvar",
    "specify_starting_values_bsvar_exh",
    "specify_starting_values_bsvar_hmsh",
    "specify_starting_values_bsvar_mix",
    "specify_starting_values_bsvar_msh",
    "specify_starting_values_bsvar_sv",
    "verify_autoregression",
    "verify_identification",
    "verify_normality",
    "verify_volatility"
  ],
  "_datasets": [
    {
      "name": "us_fiscal_cond_forecasts",
      "title": "A matrix to be used in a conditional forecasting example including the projected values of total tax revenue that are projected to increase at an average quarterly sample growth rate. The other two columns are filled with 'NA' values, which implies that the future values of the corresponding endogenous variables, namely government spending and GDP, will be forecasted given the provided projected values of total tax revenue. The matrix includes future values for the forecast horizon of two years for the US fiscal model for the period 2024 Q3 - 2026 Q1.",
      "object": "us_fiscal_cond_forecasts",
      "class": [
        "mts",
        "ts",
        "matrix",
        "array"
      ],
      "fields": [
        "ttr",
        "gs",
        "gdp"
      ],
      "rows": 8,
      "table": true,
      "tojson": true
    },
    {
      "name": "us_fiscal_ex",
      "title": "A 3-variable system of exogenous variables for the US fiscal model for the period 1948 Q1 - 2026 Q1",
      "object": "us_fiscal_ex",
      "class": [
        "mts",
        "ts",
        "matrix",
        "array"
      ],
      "fields": [
        "linear",
        "quadratic",
        "dummy_1975Q2"
      ],
      "rows": 313,
      "table": true,
      "tojson": true
    },
    {
      "name": "us_fiscal_ex_forecasts",
      "title": "A 3-variable system of exogenous variables' future values for the forecast horizon of two years for the US fiscal model for the period 2026 Q2 - 2028 Q1",
      "object": "us_fiscal_ex_forecasts",
      "class": [
        "mts",
        "ts",
        "matrix",
        "array"
      ],
      "fields": [
        "linear",
        "quadratic",
        "dummy_1975Q2"
      ],
      "rows": 8,
      "table": true,
      "tojson": true
    },
    {
      "name": "us_fiscal_lsuw",
      "title": "A 3-variable US fiscal system for the period 1948 Q1 - 2026 Q1",
      "object": "us_fiscal_lsuw",
      "class": [
        "mts",
        "ts",
        "matrix",
        "array"
      ],
      "fields": [
        "ttr",
        "gs",
        "gdp"
      ],
      "rows": 313,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "bsvars-package",
      "title": "Bayesian Estimation of Structural Vector Autoregressive Models",
      "topics": [
        "bsvars-package",
        "bsvars"
      ]
    },
    {
      "page": "compute_conditional_sd",
      "title": "Computes posterior draws of structural shock conditional standard deviations",
      "topics": [
        "compute_conditional_sd"
      ]
    },
    {
      "page": "compute_conditional_sd.PosteriorBSVAR",
      "title": "Computes posterior draws of structural shock conditional standard deviations",
      "topics": [
        "compute_conditional_sd.PosteriorBSVAR"
      ]
    },
    {
      "page": "compute_conditional_sd.PosteriorBSVAREXH",
      "title": "Computes posterior draws of structural shock conditional standard deviations",
      "topics": [
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      ]
    },
    {
      "page": "compute_conditional_sd.PosteriorBSVARHMSH",
      "title": "Computes posterior draws of structural shock conditional standard deviations",
      "topics": [
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      ]
    },
    {
      "page": "compute_conditional_sd.PosteriorBSVARMIX",
      "title": "Computes posterior draws of structural shock conditional standard deviations",
      "topics": [
        "compute_conditional_sd.PosteriorBSVARMIX"
      ]
    },
    {
      "page": "compute_conditional_sd.PosteriorBSVARMSH",
      "title": "Computes posterior draws of structural shock conditional standard deviations",
      "topics": [
        "compute_conditional_sd.PosteriorBSVARMSH"
      ]
    },
    {
      "page": "compute_conditional_sd.PosteriorBSVARSV",
      "title": "Computes posterior draws of structural shock conditional standard deviations",
      "topics": [
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      ]
    },
    {
      "page": "compute_conditional_sd.PosteriorBSVART",
      "title": "Computes posterior draws of structural shock conditional standard deviations",
      "topics": [
        "compute_conditional_sd.PosteriorBSVART"
      ]
    },
    {
      "page": "compute_fitted_values",
      "title": "Computes posterior draws from data predictive density",
      "topics": [
        "compute_fitted_values"
      ]
    },
    {
      "page": "compute_fitted_values.PosteriorBSVAR",
      "title": "Computes posterior draws from data predictive density",
      "topics": [
        "compute_fitted_values.PosteriorBSVAR"
      ]
    },
    {
      "page": "compute_fitted_values.PosteriorBSVAREXH",
      "title": "Computes posterior draws from data predictive density",
      "topics": [
        "compute_fitted_values.PosteriorBSVAREXH"
      ]
    },
    {
      "page": "compute_fitted_values.PosteriorBSVARHMSH",
      "title": "Computes posterior draws from data predictive density",
      "topics": [
        "compute_fitted_values.PosteriorBSVARHMSH"
      ]
    },
    {
      "page": "compute_fitted_values.PosteriorBSVARMIX",
      "title": "Computes posterior draws from data predictive density",
      "topics": [
        "compute_fitted_values.PosteriorBSVARMIX"
      ]
    },
    {
      "page": "compute_fitted_values.PosteriorBSVARMSH",
      "title": "Computes posterior draws from data predictive density",
      "topics": [
        "compute_fitted_values.PosteriorBSVARMSH"
      ]
    },
    {
      "page": "compute_fitted_values.PosteriorBSVARSV",
      "title": "Computes posterior draws from data predictive density",
      "topics": [
        "compute_fitted_values.PosteriorBSVARSV"
      ]
    },
    {
      "page": "compute_fitted_values.PosteriorBSVART",
      "title": "Computes posterior draws from data predictive density",
      "topics": [
        "compute_fitted_values.PosteriorBSVART"
      ]
    },
    {
      "page": "compute_historical_decompositions",
      "title": "Computes posterior draws of historical decompositions",
      "topics": [
        "compute_historical_decompositions"
      ]
    },
    {
      "page": "compute_historical_decompositions.PosteriorBSVAR",
      "title": "Computes posterior draws of historical decompositions",
      "topics": [
        "compute_historical_decompositions.PosteriorBSVAR"
      ]
    },
    {
      "page": "compute_historical_decompositions.PosteriorBSVAREXH",
      "title": "Computes posterior draws of historical decompositions",
      "topics": [
        "compute_historical_decompositions.PosteriorBSVAREXH"
      ]
    },
    {
      "page": "compute_historical_decompositions.PosteriorBSVARHMSH",
      "title": "Computes posterior draws of historical decompositions",
      "topics": [
        "compute_historical_decompositions.PosteriorBSVARHMSH"
      ]
    },
    {
      "page": "compute_historical_decompositions.PosteriorBSVARMIX",
      "title": "Computes posterior draws of historical decompositions",
      "topics": [
        "compute_historical_decompositions.PosteriorBSVARMIX"
      ]
    },
    {
      "page": "compute_historical_decompositions.PosteriorBSVARMSH",
      "title": "Computes posterior draws of historical decompositions",
      "topics": [
        "compute_historical_decompositions.PosteriorBSVARMSH"
      ]
    },
    {
      "page": "compute_historical_decompositions.PosteriorBSVARSV",
      "title": "Computes posterior draws of historical decompositions",
      "topics": [
        "compute_historical_decompositions.PosteriorBSVARSV"
      ]
    },
    {
      "page": "compute_historical_decompositions.PosteriorBSVART",
      "title": "Computes posterior draws of historical decompositions",
      "topics": [
        "compute_historical_decompositions.PosteriorBSVART"
      ]
    },
    {
      "page": "compute_impulse_responses",
      "title": "Computes posterior draws of impulse responses",
      "topics": [
        "compute_impulse_responses"
      ]
    },
    {
      "page": "compute_impulse_responses.PosteriorBSVAR",
      "title": "Computes posterior draws of impulse responses",
      "topics": [
        "compute_impulse_responses.PosteriorBSVAR"
      ]
    },
    {
      "page": "compute_impulse_responses.PosteriorBSVAREXH",
      "title": "Computes posterior draws of impulse responses",
      "topics": [
        "compute_impulse_responses.PosteriorBSVAREXH"
      ]
    },
    {
      "page": "compute_impulse_responses.PosteriorBSVARHMSH",
      "title": "Computes posterior draws of impulse responses",
      "topics": [
        "compute_impulse_responses.PosteriorBSVARHMSH"
      ]
    },
    {
      "page": "compute_impulse_responses.PosteriorBSVARMIX",
      "title": "Computes posterior draws of impulse responses",
      "topics": [
        "compute_impulse_responses.PosteriorBSVARMIX"
      ]
    },
    {
      "page": "compute_impulse_responses.PosteriorBSVARMSH",
      "title": "Computes posterior draws of impulse responses",
      "topics": [
        "compute_impulse_responses.PosteriorBSVARMSH"
      ]
    },
    {
      "page": "compute_impulse_responses.PosteriorBSVARSV",
      "title": "Computes posterior draws of impulse responses",
      "topics": [
        "compute_impulse_responses.PosteriorBSVARSV"
      ]
    },
    {
      "page": "compute_impulse_responses.PosteriorBSVART",
      "title": "Computes posterior draws of impulse responses",
      "topics": [
        "compute_impulse_responses.PosteriorBSVART"
      ]
    },
    {
      "page": "compute_regime_probabilities",
      "title": "Computes posterior draws of regime probabilities",
      "topics": [
        "compute_regime_probabilities"
      ]
    },
    {
      "page": "compute_regime_probabilities.PosteriorBSVAREXH",
      "title": "Computes posterior draws of regime probabilities",
      "topics": [
        "compute_regime_probabilities.PosteriorBSVAREXH"
      ]
    },
    {
      "page": "compute_regime_probabilities.PosteriorBSVARHMSH",
      "title": "Computes posterior draws of regime probabilities",
      "topics": [
        "compute_regime_probabilities.PosteriorBSVARHMSH"
      ]
    },
    {
      "page": "compute_regime_probabilities.PosteriorBSVARMIX",
      "title": "Computes posterior draws of regime probabilities",
      "topics": [
        "compute_regime_probabilities.PosteriorBSVARMIX"
      ]
    },
    {
      "page": "compute_regime_probabilities.PosteriorBSVARMSH",
      "title": "Computes posterior draws of regime probabilities",
      "topics": [
        "compute_regime_probabilities.PosteriorBSVARMSH"
      ]
    },
    {
      "page": "compute_structural_shocks",
      "title": "Computes posterior draws of structural shocks",
      "topics": [
        "compute_structural_shocks"
      ]
    },
    {
      "page": "compute_structural_shocks.PosteriorBSVAR",
      "title": "Computes posterior draws of structural shocks",
      "topics": [
        "compute_structural_shocks.PosteriorBSVAR"
      ]
    },
    {
      "page": "compute_structural_shocks.PosteriorBSVAREXH",
      "title": "Computes posterior draws of structural shocks",
      "topics": [
        "compute_structural_shocks.PosteriorBSVAREXH"
      ]
    },
    {
      "page": "compute_structural_shocks.PosteriorBSVARHMSH",
      "title": "Computes posterior draws of structural shocks",
      "topics": [
        "compute_structural_shocks.PosteriorBSVARHMSH"
      ]
    },
    {
      "page": "compute_structural_shocks.PosteriorBSVARMIX",
      "title": "Computes posterior draws of structural shocks",
      "topics": [
        "compute_structural_shocks.PosteriorBSVARMIX"
      ]
    },
    {
      "page": "compute_structural_shocks.PosteriorBSVARMSH",
      "title": "Computes posterior draws of structural shocks",
      "topics": [
        "compute_structural_shocks.PosteriorBSVARMSH"
      ]
    },
    {
      "page": "compute_structural_shocks.PosteriorBSVARSV",
      "title": "Computes posterior draws of structural shocks",
      "topics": [
        "compute_structural_shocks.PosteriorBSVARSV"
      ]
    },
    {
      "page": "compute_structural_shocks.PosteriorBSVART",
      "title": "Computes posterior draws of structural shocks",
      "topics": [
        "compute_structural_shocks.PosteriorBSVART"
      ]
    },
    {
      "page": "compute_variance_decompositions",
      "title": "Computes posterior draws of the forecast error variance decomposition",
      "topics": [
        "compute_variance_decompositions"
      ]
    },
    {
      "page": "compute_variance_decompositions.PosteriorBSVAR",
      "title": "Computes posterior draws of the forecast error variance decomposition",
      "topics": [
        "compute_variance_decompositions.PosteriorBSVAR"
      ]
    },
    {
      "page": "compute_variance_decompositions.PosteriorBSVAREXH",
      "title": "Computes posterior draws of the forecast error variance decomposition",
      "topics": [
        "compute_variance_decompositions.PosteriorBSVAREXH"
      ]
    },
    {
      "page": "compute_variance_decompositions.PosteriorBSVARHMSH",
      "title": "Computes posterior draws of the forecast error variance decomposition",
      "topics": [
        "compute_variance_decompositions.PosteriorBSVARHMSH"
      ]
    },
    {
      "page": "compute_variance_decompositions.PosteriorBSVARMIX",
      "title": "Computes posterior draws of the forecast error variance decomposition",
      "topics": [
        "compute_variance_decompositions.PosteriorBSVARMIX"
      ]
    },
    {
      "page": "compute_variance_decompositions.PosteriorBSVARMSH",
      "title": "Computes posterior draws of the forecast error variance decomposition",
      "topics": [
        "compute_variance_decompositions.PosteriorBSVARMSH"
      ]
    },
    {
      "page": "compute_variance_decompositions.PosteriorBSVARSV",
      "title": "Computes posterior draws of the forecast error variance decomposition",
      "topics": [
        "compute_variance_decompositions.PosteriorBSVARSV"
      ]
    },
    {
      "page": "compute_variance_decompositions.PosteriorBSVART",
      "title": "Computes posterior draws of the forecast error variance decomposition",
      "topics": [
        "compute_variance_decompositions.PosteriorBSVART"
      ]
    },
    {
      "page": "estimate",
      "title": "Bayesian estimation of Structural Vector Autoregressions via Gibbs sampler",
      "topics": [
        "estimate"
      ]
    },
    {
      "page": "estimate.BSVAR",
      "title": "Bayesian estimation of a homoskedastic Structural Vector Autoregression via Gibbs sampler",
      "topics": [
        "estimate.BSVAR"
      ]
    },
    {
      "page": "estimate.BSVAREXH",
      "title": "Bayesian estimation of a Structural Vector Autoregression with exogenous heteroskedastic regime changes via Gibbs sampler",
      "topics": [
        "estimate.BSVAREXH"
      ]
    },
    {
      "page": "estimate.BSVARHMSH",
      "title": "Bayesian estimation of a Structural Vector Autoregression with Heterogeneous Markov-switching heteroskedasticity via Gibbs sampler",
      "topics": [
        "estimate.BSVARHMSH"
      ]
    },
    {
      "page": "estimate.BSVARMIX",
      "title": "Bayesian estimation of a Structural Vector Autoregression with shocks following a finite mixture of normal components via Gibbs sampler",
      "topics": [
        "estimate.BSVARMIX"
      ]
    },
    {
      "page": "estimate.BSVARMSH",
      "title": "Bayesian estimation of a Structural Vector Autoregression with Markov-switching heteroskedasticity via Gibbs sampler",
      "topics": [
        "estimate.BSVARMSH"
      ]
    },
    {
      "page": "estimate.BSVARSV",
      "title": "Bayesian estimation of a Structural Vector Autoregression with Stochastic Volatility heteroskedasticity via Gibbs sampler",
      "topics": [
        "estimate.BSVARSV"
      ]
    },
    {
      "page": "estimate.BSVART",
      "title": "Bayesian estimation of a homoskedastic Structural Vector Autoregression with t-distributed structural shocks via Gibbs sampler",
      "topics": [
        "estimate.BSVART"
      ]
    },
    {
      "page": "estimate.PosteriorBSVAR",
      "title": "Bayesian estimation of a homoskedastic Structural Vector Autoregression via Gibbs sampler",
      "topics": [
        "estimate.PosteriorBSVAR"
      ]
    },
    {
      "page": "estimate.PosteriorBSVAREXH",
      "title": "Bayesian estimation of a Structural Vector Autoregression with exogenous heteroskedastic regime changes via Gibbs sampler",
      "topics": [
        "estimate.PosteriorBSVAREXH"
      ]
    },
    {
      "page": "estimate.PosteriorBSVARHMSH",
      "title": "Bayesian estimation of a Structural Vector Autoregression with Heterogeneous Markov-switching heteroskedasticity via Gibbs sampler",
      "topics": [
        "estimate.PosteriorBSVARHMSH"
      ]
    },
    {
      "page": "estimate.PosteriorBSVARMIX",
      "title": "Bayesian estimation of a Structural Vector Autoregression with shocks following a finite mixture of normal components via Gibbs sampler",
      "topics": [
        "estimate.PosteriorBSVARMIX"
      ]
    },
    {
      "page": "estimate.PosteriorBSVARMSH",
      "title": "Bayesian estimation of a Structural Vector Autoregression with Markov-switching heteroskedasticity via Gibbs sampler",
      "topics": [
        "estimate.PosteriorBSVARMSH"
      ]
    },
    {
      "page": "estimate.PosteriorBSVARSV",
      "title": "Bayesian estimation of a Structural Vector Autoregression with Stochastic Volatility heteroskedasticity via Gibbs sampler",
      "topics": [
        "estimate.PosteriorBSVARSV"
      ]
    },
    {
      "page": "estimate.PosteriorBSVART",
      "title": "Bayesian estimation of a homoskedastic Structural Vector Autoregression with t-distributed structural shocks via Gibbs sampler",
      "topics": [
        "estimate.PosteriorBSVART"
      ]
    },
    {
      "page": "forecast.PosteriorBSVAR",
      "title": "Forecasting using Bayesian Structural Vector Autoregression",
      "topics": [
        "forecast.PosteriorBSVAR"
      ]
    },
    {
      "page": "forecast.PosteriorBSVAREXH",
      "title": "Forecasting using Bayesian Structural Vector Autoregression",
      "topics": [
        "forecast.PosteriorBSVAREXH"
      ]
    },
    {
      "page": "forecast.PosteriorBSVARHMSH",
      "title": "Forecasting using Bayesian Structural Vector Autoregression",
      "topics": [
        "forecast.PosteriorBSVARHMSH"
      ]
    },
    {
      "page": "forecast.PosteriorBSVARMIX",
      "title": "Forecasting using Bayesian Structural Vector Autoregression",
      "topics": [
        "forecast.PosteriorBSVARMIX"
      ]
    },
    {
      "page": "forecast.PosteriorBSVARMSH",
      "title": "Forecasting using Bayesian Structural Vector Autoregression",
      "topics": [
        "forecast.PosteriorBSVARMSH"
      ]
    },
    {
      "page": "forecast.PosteriorBSVARSV",
      "title": "Forecasting using Bayesian Structural Vector Autoregression",
      "topics": [
        "forecast.PosteriorBSVARSV"
      ]
    },
    {
      "page": "forecast.PosteriorBSVART",
      "title": "Forecasting using Bayesian Structural Vector Autoregression",
      "topics": [
        "forecast.PosteriorBSVART"
      ]
    },
    {
      "page": "normalise",
      "title": "Waggoner & Zha (2003) row signs normalisation of the posterior draws for the structural matrix B",
      "topics": [
        "normalise"
      ]
    },
    {
      "page": "normalise.PosteriorBSVAR",
      "title": "Waggoner & Zha (2003) row signs normalisation of the posterior draws for the structural matrix B",
      "topics": [
        "normalise.PosteriorBSVAR"
      ]
    },
    {
      "page": "normalise.PosteriorBSVAREXH",
      "title": "Waggoner & Zha (2003) row signs normalisation of the posterior draws for the structural matrix B",
      "topics": [
        "normalise.PosteriorBSVAREXH"
      ]
    },
    {
      "page": "normalise.PosteriorBSVARHMSH",
      "title": "Waggoner & Zha (2003) row signs normalisation of the posterior draws for the structural matrix B",
      "topics": [
        "normalise.PosteriorBSVARHMSH"
      ]
    },
    {
      "page": "normalise.PosteriorBSVARMIX",
      "title": "Waggoner & Zha (2003) row signs normalisation of the posterior draws for the structural matrix B",
      "topics": [
        "normalise.PosteriorBSVARMIX"
      ]
    },
    {
      "page": "normalise.PosteriorBSVARMSH",
      "title": "Waggoner & Zha (2003) row signs normalisation of the posterior draws for the structural matrix B",
      "topics": [
        "normalise.PosteriorBSVARMSH"
      ]
    },
    {
      "page": "normalise.PosteriorBSVARSV",
      "title": "Waggoner & Zha (2003) row signs normalisation of the posterior draws for the structural matrix B",
      "topics": [
        "normalise.PosteriorBSVARSV"
      ]
    },
    {
      "page": "normalise.PosteriorBSVART",
      "title": "Waggoner & Zha (2003) row signs normalisation of the posterior draws for the structural matrix B",
      "topics": [
        "normalise.PosteriorBSVART"
      ]
    },
    {
      "page": "plot_ribbon",
      "title": "Plots the median and an interval between two specified percentiles for a sequence of 'K' random variables",
      "topics": [
        "plot_ribbon"
      ]
    },
    {
      "page": "plot.Forecasts",
      "title": "Plots fitted values of dependent variables",
      "topics": [
        "plot.Forecasts"
      ]
    },
    {
      "page": "plot.PosteriorFEVD",
      "title": "Plots forecast error variance decompositions",
      "topics": [
        "plot.PosteriorFEVD"
      ]
    },
    {
      "page": "plot.PosteriorFitted",
      "title": "Plots fitted values of dependent variables",
      "topics": [
        "plot.PosteriorFitted"
      ]
    },
    {
      "page": "plot.PosteriorHD",
      "title": "Plots historical decompositions",
      "topics": [
        "plot.PosteriorHD"
      ]
    },
    {
      "page": "plot.PosteriorIR",
      "title": "Plots impulse responses",
      "topics": [
        "plot.PosteriorIR"
      ]
    },
    {
      "page": "plot.PosteriorRegimePr",
      "title": "Plots estimated regime probabilities",
      "topics": [
        "plot.PosteriorRegimePr"
      ]
    },
    {
      "page": "plot.PosteriorShocks",
      "title": "Plots structural shocks",
      "topics": [
        "plot.PosteriorShocks"
      ]
    },
    {
      "page": "plot.PosteriorSigma",
      "title": "Plots structural shocks' conditional standard deviations",
      "topics": [
        "plot.PosteriorSigma"
      ]
    },
    {
      "page": "specify_bsvar",
      "title": "R6 Class representing the specification of the homoskedastic BSVAR model",
      "topics": [
        "specify_bsvar"
      ]
    },
    {
      "page": "specify_bsvar_exh",
      "title": "R6 Class representing the specification of the BSVAREXH model with exogenous heteroskedastic regime change.",
      "topics": [
        "specify_bsvar_exh"
      ]
    },
    {
      "page": "specify_bsvar_hmsh",
      "title": "R6 Class representing the specification of the BSVARHMSH model with Heterogeneous Markov Switching Heteroskedasticity.",
      "topics": [
        "specify_bsvar_hmsh"
      ]
    },
    {
      "page": "specify_bsvar_mix",
      "title": "R6 Class representing the specification of the BSVAR model with a zero-mean mixture of normals model for structural shocks.",
      "topics": [
        "specify_bsvar_mix"
      ]
    },
    {
      "page": "specify_bsvar_msh",
      "title": "R6 Class representing the specification of the BSVAR model with Markov Switching Heteroskedasticity.",
      "topics": [
        "specify_bsvar_msh"
      ]
    },
    {
      "page": "specify_bsvar_sv",
      "title": "R6 Class representing the specification of the BSVAR model with Stochastic Volatility heteroskedasticity.",
      "topics": [
        "specify_bsvar_sv"
      ]
    },
    {
      "page": "specify_bsvar_t",
      "title": "R6 Class representing the specification of the BSVAR model with t-distributed structural shocks.",
      "topics": [
        "specify_bsvar_t"
      ]
    },
    {
      "page": "specify_data_matrices",
      "title": "R6 Class Representing DataMatricesBSVAR",
      "topics": [
        "specify_data_matrices"
      ]
    },
    {
      "page": "specify_identification_bsvars",
      "title": "R6 Class Representing IdentificationBSVARs",
      "topics": [
        "specify_identification_bsvars"
      ]
    },
    {
      "page": "specify_posterior_bsvar",
      "title": "R6 Class Representing PosteriorBSVAR",
      "topics": [
        "specify_posterior_bsvar"
      ]
    },
    {
      "page": "specify_posterior_bsvar_exh",
      "title": "R6 Class Representing PosteriorBSVAREXH",
      "topics": [
        "specify_posterior_bsvar_exh"
      ]
    },
    {
      "page": "specify_posterior_bsvar_hmsh",
      "title": "R6 Class Representing PosteriorBSVARHMSH",
      "topics": [
        "specify_posterior_bsvar_hmsh"
      ]
    },
    {
      "page": "specify_posterior_bsvar_mix",
      "title": "R6 Class Representing PosteriorBSVARMIX",
      "topics": [
        "specify_posterior_bsvar_mix"
      ]
    },
    {
      "page": "specify_posterior_bsvar_msh",
      "title": "R6 Class Representing PosteriorBSVARMSH",
      "topics": [
        "specify_posterior_bsvar_msh"
      ]
    },
    {
      "page": "specify_posterior_bsvar_sv",
      "title": "R6 Class Representing PosteriorBSVARSV",
      "topics": [
        "specify_posterior_bsvar_sv"
      ]
    },
    {
      "page": "specify_posterior_bsvar_t",
      "title": "R6 Class Representing PosteriorBSVART",
      "topics": [
        "specify_posterior_bsvar_t"
      ]
    },
    {
      "page": "specify_prior_bsvar",
      "title": "R6 Class Representing PriorBSVAR",
      "topics": [
        "specify_prior_bsvar"
      ]
    },
    {
      "page": "specify_prior_bsvar_exh",
      "title": "R6 Class Representing PriorBSVAREXH",
      "topics": [
        "specify_prior_bsvar_exh"
      ]
    },
    {
      "page": "specify_prior_bsvar_mix",
      "title": "R6 Class Representing PriorBSVARMIX",
      "topics": [
        "specify_prior_bsvar_mix"
      ]
    },
    {
      "page": "specify_prior_bsvar_msh",
      "title": "R6 Class Representing PriorBSVARMSH",
      "topics": [
        "specify_prior_bsvar_msh"
      ]
    },
    {
      "page": "specify_prior_bsvar_sv",
      "title": "R6 Class Representing PriorBSVARSV",
      "topics": [
        "specify_prior_bsvar_sv"
      ]
    },
    {
      "page": "specify_prior_bsvar_t",
      "title": "R6 Class Representing PriorBSVART",
      "topics": [
        "specify_prior_bsvar_t"
      ]
    },
    {
      "page": "specify_starting_values_bsvar",
      "title": "R6 Class Representing StartingValuesBSVAR",
      "topics": [
        "specify_starting_values_bsvar"
      ]
    },
    {
      "page": "specify_starting_values_bsvar_exh",
      "title": "R6 Class Representing StartingValuesBSVAREXH",
      "topics": [
        "specify_starting_values_bsvar_exh"
      ]
    },
    {
      "page": "specify_starting_values_bsvar_hmsh",
      "title": "R6 Class Representing StartingValuesBSVAHMSH",
      "topics": [
        "specify_starting_values_bsvar_hmsh"
      ]
    },
    {
      "page": "specify_starting_values_bsvar_mix",
      "title": "R6 Class Representing StartingValuesBSVARMIX",
      "topics": [
        "specify_starting_values_bsvar_mix"
      ]
    },
    {
      "page": "specify_starting_values_bsvar_msh",
      "title": "R6 Class Representing StartingValuesBSVARMSH",
      "topics": [
        "specify_starting_values_bsvar_msh"
      ]
    },
    {
      "page": "specify_starting_values_bsvar_sv",
      "title": "R6 Class Representing StartingValuesBSVARSV",
      "topics": [
        "specify_starting_values_bsvar_sv"
      ]
    },
    {
      "page": "summary.Forecasts",
      "title": "Provides posterior summary of Forecasts",
      "topics": [
        "summary.Forecasts"
      ]
    },
    {
      "page": "summary.PosteriorBSVAR",
      "title": "Provides posterior summary of homoskedastic Structural VAR estimation",
      "topics": [
        "summary.PosteriorBSVAR"
      ]
    },
    {
      "page": "summary.PosteriorBSVAREXH",
      "title": "Provides posterior summary of heteroskedastic Structural VAR estimation",
      "topics": [
        "summary.PosteriorBSVAREXH"
      ]
    },
    {
      "page": "summary.PosteriorBSVARHMSH",
      "title": "Provides posterior summary of heteroskedastic Structural VAR estimation",
      "topics": [
        "summary.PosteriorBSVARHMSH"
      ]
    },
    {
      "page": "summary.PosteriorBSVARMIX",
      "title": "Provides posterior summary of non-normal Structural VAR estimation",
      "topics": [
        "summary.PosteriorBSVARMIX"
      ]
    },
    {
      "page": "summary.PosteriorBSVARMSH",
      "title": "Provides posterior summary of heteroskedastic Structural VAR estimation",
      "topics": [
        "summary.PosteriorBSVARMSH"
      ]
    },
    {
      "page": "summary.PosteriorBSVARSV",
      "title": "Provides posterior summary of heteroskedastic Structural VAR estimation",
      "topics": [
        "summary.PosteriorBSVARSV"
      ]
    },
    {
      "page": "summary.PosteriorBSVART",
      "title": "Provides posterior summary of Structural VAR with t-distributed shocks estimation",
      "topics": [
        "summary.PosteriorBSVART"
      ]
    },
    {
      "page": "summary.PosteriorFEVD",
      "title": "Provides posterior summary of forecast error variance decompositions",
      "topics": [
        "summary.PosteriorFEVD"
      ]
    },
    {
      "page": "summary.PosteriorFitted",
      "title": "Provides posterior summary of variables' fitted values",
      "topics": [
        "summary.PosteriorFitted"
      ]
    },
    {
      "page": "summary.PosteriorHD",
      "title": "Provides posterior summary of historical decompositions",
      "topics": [
        "summary.PosteriorHD"
      ]
    },
    {
      "page": "summary.PosteriorIR",
      "title": "Provides posterior summary of impulse responses",
      "topics": [
        "summary.PosteriorIR"
      ]
    },
    {
      "page": "summary.PosteriorRegimePr",
      "title": "Provides posterior summary of regime probabilities",
      "topics": [
        "summary.PosteriorRegimePr"
      ]
    },
    {
      "page": "summary.PosteriorShocks",
      "title": "Provides posterior summary of structural shocks",
      "topics": [
        "summary.PosteriorShocks"
      ]
    },
    {
      "page": "summary.PosteriorSigma",
      "title": "Provides posterior summary of structural shocks' conditional standard deviations",
      "topics": [
        "summary.PosteriorSigma"
      ]
    },
    {
      "page": "summary.SDDRautoregression",
      "title": "Provides summary of verifying hypotheses about autoregressive parameters",
      "topics": [
        "summary.SDDRautoregression"
      ]
    },
    {
      "page": "summary.SDDRidMIX",
      "title": "Provides summary of verifying shocks' normality",
      "topics": [
        "summary.SDDRidMIX"
      ]
    },
    {
      "page": "summary.SDDRidMSH",
      "title": "Provides summary of verifying homoskedasticity",
      "topics": [
        "summary.SDDRidMSH"
      ]
    },
    {
      "page": "summary.SDDRidSV",
      "title": "Provides summary of verifying homoskedasticity",
      "topics": [
        "summary.SDDRidSV"
      ]
    },
    {
      "page": "summary.SDDRidT",
      "title": "Provides summary of verifying shocks' normality",
      "topics": [
        "summary.SDDRidT"
      ]
    },
    {
      "page": "summary.SDDRvolatility",
      "title": "Provides summary of verifying homoskedasticity",
      "topics": [
        "summary.SDDRvolatility"
      ]
    },
    {
      "page": "us_fiscal_cond_forecasts",
      "title": "A matrix to be used in a conditional forecasting example including the projected values of total tax revenue that are projected to increase at an average quarterly sample growth rate. The other two columns are filled with 'NA' values, which implies that the future values of the corresponding endogenous variables, namely government spending and GDP, will be forecasted given the provided projected values of total tax revenue. The matrix includes future values for the forecast horizon of two years for the US fiscal model for the period 2024 Q3 - 2026 Q1.",
      "topics": [
        "us_fiscal_cond_forecasts"
      ]
    },
    {
      "page": "us_fiscal_ex",
      "title": "A 3-variable system of exogenous variables for the US fiscal model for the period 1948 Q1 - 2026 Q1",
      "topics": [
        "us_fiscal_ex"
      ]
    },
    {
      "page": "us_fiscal_ex_forecasts",
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