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  "Package": "APRScenario",
  "Title": "Structural Scenario Analysis for Bayesian Structural Vector\nAutoregression Models",
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  "Author": "Giovanni Lombardo [aut, cre]",
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      "title": "big_b_and_M This function returns the extended b and M matrices as in APR",
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      "title": "KL function APR suggest this measure to assess the \"plausibility\" of the conditional forecast. It is based on the Kullback-Leibler measure of distance between the unconditional forecast and the conditional/scenario forecast.",
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      "title": "mat_forc function ############################################################################## NB: HERE WE USE Antolin-Diaz et al notation # B is reduced form; # A is structural; # d is intercepts # M is reduced so that E(u_u')=Sigma=(A_0_A_0')^(-1) and M_0=A_0^(-1)*Q # Note that the code returns conflicting notation: # B=>A_0^(-1)*Q and # A=>B # ##############################################################################",
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        "scenarios"
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        "SimScen"
      ]
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