{
  "_id": "6aaba3a33d719c1f8406cbae",
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  "Type": "Package",
  "Title": "Vector Logistic Smooth Transition Models Estimation and\nPrediction",
  "Version": "1.1.10",
  "Authors@R": "c(\nperson(\"Andrea\", \"Bucci\", email = \"andrea.bucci@unich.it\", role = c(\"aut\", \"cre\", \"cph\")),\nperson(\"Giulio\", \"Palomba\", role = \"aut\"),\nperson(\"Eduardo\", \"Rossi\", role = \"aut\"),\nperson(\"Andrea\", \"Faragalli\", role = \"ctb\")\n)",
  "Description": "Allows the user to estimate a vector logistic smooth\ntransition autoregressive model via maximum log-likelihood or\nnonlinear least squares. It further permits to test for\nlinearity in the multivariate framework against a vector\nlogistic smooth transition autoregressive model with a single\ntransition variable. The estimation method is discussed in\nTerasvirta and Yang (2014,\n<doi:10.1108/S0731-9053(2013)0000031008>). Also, realized\ncovariances can be constructed from stock market prices or\nreturns, as explained in Andersen et al. (2001,\n<doi:10.1016/S0304-405X(01)00055-1>).",
  "License": "GPL",
  "Encoding": "UTF-8",
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  "URL": "https://github.com/andbucci/starvars",
  "RoxygenNote": "7.1.1",
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  "Repository": "https://andbucci.r-universe.dev",
  "Date/Publication": "2022-01-17 17:03:29 UTC",
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    "User": "root"
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  "Author": "Andrea Bucci [aut, cre, cph],\nGiulio Palomba [aut],\nEduardo Rossi [aut],\nAndrea Faragalli [ctb]",
  "Maintainer": "Andrea Bucci <andrea.bucci@unich.it>",
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    "startingVLSTAR",
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        "SP-NIKKEI",
        "SP-FTSE",
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        "NIKKEI-FTSE",
        "NIKKEI-DAX",
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        "Inf_GER"
      ],
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        "zoo"
      ],
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        "stock2",
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        "stock7",
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        "zoo"
      ],
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        "Microsoft",
        "Amazon"
      ],
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      "tojson": false
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      "page": "coef.VLSTAR",
      "title": "Coefficient method for objects of class VLSTAR",
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        "coef.VLSTAR",
        "coefficients"
      ]
    },
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      "page": "logLik.VLSTAR",
      "title": "Log-Likelihood method",
      "topics": [
        "logLik",
        "logLik.VLSTAR"
      ]
    },
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      "title": "Long-run variance using Bartlett kernel",
      "topics": [
        "lrvarbart"
      ]
    },
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      "title": "Multivariate CUMSUM test",
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        "multiCUMSUM",
        "print.multiCUMSUM"
      ]
    },
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      ]
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        "print.VLSTAR"
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      "title": "VLSTAR- Estimation",
      "topics": [
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