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  "Title": "Estimate Univariate Gaussian and Student's t Mixture\nAutoregressive Models",
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  "Author": "Savi Virolainen [aut, cre]\n(<https://orcid.org/0000-0002-5075-6821>)",
  "Description": "Maximum likelihood estimation of univariate Gaussian\nMixture Autoregressive (GMAR), Student's t Mixture\nAutoregressive (StMAR), and Gaussian and Student's t Mixture\nAutoregressive (G-StMAR) models, quantile residual tests,\ngraphical diagnostics, forecast and simulate from GMAR, StMAR\nand G-StMAR processes. Leena Kalliovirta, Mika Meitz, Pentti\nSaikkonen (2015) <doi:10.1111/jtsa.12108>, Mika Meitz, Daniel\nPreve, Pentti Saikkonen (2023)\n<doi:10.1080/03610926.2021.1916531>, Savi Virolainen (2022)\n<doi:10.1515/snde-2020-0060>.",
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    "calc_hessian",
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    "cond_moments",
    "diagnostic_plot",
    "fitGSMAR",
    "GAfit",
    "get_ar_roots",
    "get_foc",
    "get_gradient",
    "get_hessian",
    "get_regime_autocovs",
    "get_regime_means",
    "get_regime_vars",
    "get_soc",
    "GSMAR",
    "is_stationary",
    "iterate_more",
    "loglikelihood",
    "LR_test",
    "mixing_weights",
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    "quantile_residuals",
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    "smart_ind",
    "stmar_to_gstmar",
    "stmarpars_to_gstmar",
    "swap_parametrization",
    "uncond_moments",
    "Wald_test"
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      "title": "Spread between 10-Year and 1-Year Treasury rates: M10Y1Y",
      "object": "M10Y1Y",
      "class": [
        "ts"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "simudata",
      "title": "Simulated data",
      "object": "simudata",
      "class": [
        "numeric"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "T10Y1Y",
      "title": "Spread between 10-Year and 1-Year Treasury rates: T10Y1Y",
      "object": "T10Y1Y",
      "class": [
        "ts"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "TBFF",
      "title": "Spread between the 3-month Treasury bill rate and the effective federal funds rate: TBFF",
      "object": "TBFF",
      "class": [
        "ts"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "uGMAR-package",
      "title": "uGMAR: Estimate Univariate Gaussian and Student's t Mixture Autoregressive Models",
      "topics": [
        "uGMAR-package",
        "uGMAR"
      ]
    },
    {
      "page": "add_data",
      "title": "Add data to object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model",
      "topics": [
        "add_data"
      ]
    },
    {
      "page": "alt_gsmar",
      "title": "Construct a GSMAR model based on results from an arbitrary estimation round of 'fitGSMAR'",
      "topics": [
        "alt_gsmar"
      ]
    },
    {
      "page": "calc_gradient",
      "title": "Calculate gradient or Hessian matrix",
      "topics": [
        "calc_gradient",
        "calc_hessian",
        "get_foc",
        "get_gradient",
        "get_hessian",
        "get_soc"
      ]
    },
    {
      "page": "cond_moment_plot",
      "title": "Conditional mean or variance plot for GMAR, StMAR, and G-StMAR models",
      "topics": [
        "cond_moment_plot"
      ]
    },
    {
      "page": "cond_moments",
      "title": "Calculate conditional moments of GMAR, StMAR, or G-StMAR model",
      "concept": [
        "moment functions"
      ],
      "topics": [
        "cond_moments"
      ]
    },
    {
      "page": "diagnostic_plot",
      "title": "Quantile residual based diagnostic plots for GMAR, StMAR, and G-StMAR models",
      "topics": [
        "diagnostic_plot"
      ]
    },
    {
      "page": "fitGSMAR",
      "title": "Estimate Gaussian or Student's t Mixture Autoregressive model",
      "topics": [
        "fitGSMAR"
      ]
    },
    {
      "page": "GAfit",
      "title": "Genetic algorithm for preliminary estimation of GMAR, StMAR, or G-StMAR model",
      "topics": [
        "GAfit"
      ]
    },
    {
      "page": "get_ar_roots",
      "title": "Calculate absolute values of the roots of the AR characteristic polynomials",
      "topics": [
        "get_ar_roots"
      ]
    },
    {
      "page": "get_regime_autocovs",
      "title": "Calculate regime specific autocovariances *gamma*_{m,p}",
      "concept": [
        "moment functions"
      ],
      "topics": [
        "get_regime_autocovs"
      ]
    },
    {
      "page": "get_regime_means",
      "title": "Calculate regime specific means mu_{m}",
      "concept": [
        "moment functions"
      ],
      "topics": [
        "get_regime_means"
      ]
    },
    {
      "page": "get_regime_vars",
      "title": "Calculate regime specific variances gamma_{m,0}",
      "concept": [
        "moment functions"
      ],
      "topics": [
        "get_regime_vars"
      ]
    },
    {
      "page": "GSMAR",
      "title": "Create object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model",
      "topics": [
        "GSMAR",
        "logLik.gsmar",
        "plot.gsmar",
        "print.gsmar",
        "residuals.gsmar",
        "summary.gsmar"
      ]
    },
    {
      "page": "is_stationary",
      "title": "Check the stationary condition of specified GMAR, StMAR, or G-StMAR model.",
      "topics": [
        "is_stationary"
      ]
    },
    {
      "page": "iterate_more",
      "title": "Maximum likelihood estimation of GMAR, StMAR, or G-StMAR model with preliminary estimates",
      "topics": [
        "iterate_more"
      ]
    },
    {
      "page": "loglikelihood",
      "title": "Compute the log-likelihood of GMAR, StMAR, or G-StMAR model",
      "topics": [
        "loglikelihood"
      ]
    },
    {
      "page": "LR_test",
      "title": "Perform likelihood ratio test",
      "topics": [
        "LR_test"
      ]
    },
    {
      "page": "M10Y1Y",
      "title": "Spread between 10-Year and 1-Year Treasury rates: M10Y1Y",
      "topics": [
        "M10Y1Y"
      ]
    },
    {
      "page": "mixing_weights",
      "title": "Calculate mixing weights of GMAR, StMAR or G-StMAR model",
      "topics": [
        "mixing_weights"
      ]
    },
    {
      "page": "pick_pars",
      "title": "Pick phi_0 (or mu), AR-coefficients, and variance parameters from a parameter vector",
      "topics": [
        "pick_pars"
      ]
    },
    {
      "page": "plot.gsmarpred",
      "title": "Plot method for class 'gsmarpred' objects",
      "topics": [
        "plot.gsmarpred"
      ]
    },
    {
      "page": "quantile_residual_tests",
      "title": "Quantile residual tests for GMAR, StMAR , and G-StMAR models",
      "topics": [
        "plot.qrtest",
        "print.qrtest",
        "quantile_residual_tests"
      ]
    },
    {
      "page": "predict.gsmar",
      "title": "Forecast GMAR, StMAR, or G-StMAR process",
      "topics": [
        "predict.gsmar"
      ]
    },
    {
      "page": "print.gsmarpred",
      "title": "Print method for class 'gsmarpred' objects",
      "topics": [
        "print.gsmarpred"
      ]
    },
    {
      "page": "print.gsmarsum",
      "title": "Print method from objects of class 'gsmarsum'",
      "topics": [
        "print.gsmarsum"
      ]
    },
    {
      "page": "profile_logliks",
      "title": "Plot profile log-likelihoods around the estimates",
      "topics": [
        "profile_logliks"
      ]
    },
    {
      "page": "quantile_residual_plot",
      "title": "Plot quantile residual time series and histogram",
      "topics": [
        "quantile_residual_plot"
      ]
    },
    {
      "page": "quantile_residuals",
      "title": "Compute quantile residuals of GMAR, StMAR, or G-StMAR model",
      "topics": [
        "quantile_residuals"
      ]
    },
    {
      "page": "random_ind",
      "title": "Create random GMAR, StMAR, or G-StMAR model compatible parameter vector",
      "topics": [
        "random_ind",
        "smart_ind"
      ]
    },
    {
      "page": "reform_parameters",
      "title": "Reform any parameter vector into standard form.",
      "topics": [
        "reform_parameters"
      ]
    },
    {
      "page": "simudata",
      "title": "Simulated data",
      "topics": [
        "simudata"
      ]
    },
    {
      "page": "simulate.gsmar",
      "title": "Simulate obsercations from GMAR, StMAR, and G-StMAR processes",
      "topics": [
        "simulate.gsmar"
      ]
    },
    {
      "page": "stmar_to_gstmar",
      "title": "Estimate a G-StMAR model based on a StMAR model with large degrees of freedom parameters",
      "topics": [
        "stmar_to_gstmar"
      ]
    },
    {
      "page": "stmarpars_to_gstmar",
      "title": "Transform a StMAR or G-StMAR model parameter vector to a corresponding G-StMAR model parameter vector with large dfs parameters reduced.",
      "topics": [
        "stmarpars_to_gstmar"
      ]
    },
    {
      "page": "swap_parametrization",
      "title": "Swap the parametrization of object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model",
      "topics": [
        "swap_parametrization"
      ]
    },
    {
      "page": "T10Y1Y",
      "title": "Spread between 10-Year and 1-Year Treasury rates: T10Y1Y",
      "topics": [
        "T10Y1Y"
      ]
    },
    {
      "page": "TBFF",
      "title": "Spread between the 3-month Treasury bill rate and the effective federal funds rate: TBFF",
      "topics": [
        "TBFF"
      ]
    },
    {
      "page": "uncond_moments",
      "title": "Calculate unconditional mean, variance, first p autocovariances and autocorrelations of the GSMAR process.",
      "concept": [
        "moment functions"
      ],
      "topics": [
        "uncond_moments"
      ]
    },
    {
      "page": "Wald_test",
      "title": "Perform Wald test",
      "topics": [
        "Wald_test"
      ]
    }
  ],
  "_readme": "https://github.com/saviviro/ugmar/raw/HEAD/README.md",
  "_rundeps": [
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    "Matrix",
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  "_vignettes": [
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      "source": "uGMARpaper.Rnw",
      "filename": "uGMARpaper.pdf",
      "title": "uGMAR: A Family of Mixture Autoregressive Models in R",
      "engine": "utils::Sweave",
      "headings": [
        "Introduction",
        "Introduction",
        "Models",
        "Models",
        "Estimation and model selection",
        "Estimation and model selection",
        "Quantile residual based model diagnostics",
        "Quantile residual based model diagnostics",
        "Building a GSMAR model with specific parameter values",
        "Building a GSMAR model with specific parameter values",
        "Simulation and forecasting",
        "Simulation and forecasting",
        "Summary",
        "Summary",
        "Computational details",
        "Acknowledgments",
        "A table of some useful functions",
        "References",
        "Simulation experiment",
        "Appendix A: Simulation experiment",
        "Closed form expressions of quantile residuals",
        "Appendix B: Closed form expressions of quantile residuals"
      ],
      "created": "2021-05-05 12:22:06",
      "modified": "2025-10-06 14:33:24",
      "commits": 23
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