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  "Title": "Time Varying GARCH Modelling",
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  "Authors@R": "c(person(given = \"Susana\",\nfamily = \"Campos-Martins\",\nrole = c(\"aut\", \"cre\"),\nemail = \"scmartins@ucp.pt\"),\nperson(given = \"Genaro\",\nfamily = \"Sucarrat\",\nrole = \"ctb\"))",
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  "Description": "Simulation, estimation and inference for univariate and\nmultivariate TV(s)-GARCH(p,q,r)-X models, where s indicates the\nnumber and shape of the transition functions, p is the ARCH\norder, q is the GARCH order, r is the asymmetry order, and 'X'\nindicates that covariates can be included; see Campos-Martins\nand Sucarrat (2024) <doi:10.18637/jss.v108.i09>. In the\nmultivariate case, variances are estimated equation by equation\nand dynamic conditional correlations are allowed. The TV\nlong-term component of the variance as in the multiplicative\nTV-GARCH model of Amado and Terasvirta (2013)\n<doi:10.1016/j.jeconom.2013.03.006> introduces non-stationarity\nwhereas the GARCH-X short-term component describes conditional\nheteroscedasticity. Maximisation by parts leads to consistent\nand asymptotically normal estimates.",
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  "URL": "https://sites.google.com/site/susanacamposmartins",
  "NeedsCompilation": "no",
  "Packaged": {
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      "title": "Time Varying GARCH Modelling",
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      "title": "Extraction functions for multivariate 'mtvgarch' objects",
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        "coef.mtvgarch",
        "fitted.mtvgarch",
        "logLik.mtvgarch",
        "nobs.mtvgarch",
        "plot.mtvgarch",
        "predict.mtvgarch",
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        "summary.mtvgarch",
        "toLatex.mtvgarch",
        "vcov.mtvgarch"
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      "title": "Extraction functions (S3 methods) for univarate 'tvgarch' objects",
      "topics": [
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        "fitted.tvgarch",
        "logLik.tvgarch",
        "nobs.tvgarch",
        "plot.tvgarch",
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        "fitted.tvgarchTest",
        "logLik.tvgarchTest",
        "nobs.tvgarchTest",
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        "combos"
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