{
  "_id": "6a23bb40530b9bc726bd9492",
  "Package": "mixAR",
  "Type": "Package",
  "Title": "Mixture Autoregressive Models",
  "Version": "0.22.8.9000",
  "Authors@R": "c( person(given = c(\"Georgi\", \"N.\"), \nfamily = \"Boshnakov\",\nrole = c(\"aut\", \"cre\"),\nemail = \"georgi.boshnakov@manchester.ac.uk\",\ncomment = c(ORCID = \"0000-0003-2839-346X\")),\nperson(given = \"Davide\",\nfamily = \"Ravagli\",\nrole = \"aut\", email = \"davide.ravagli@manchester.ac.uk\",\ncomment = c(ORCID = \"0000-0001-7146-7685\")) )",
  "Description": "Model time series using mixture autoregressive (MAR)\nmodels.  Implemented are frequentist (EM) and Bayesian methods\nfor estimation, prediction and model evaluation. See Wong and\nLi (2002) <doi:10.1111/1467-9868.00222>, Boshnakov (2009)\n<doi:10.1016/j.spl.2009.04.009>), and the extensive references\nin the documentation.",
  "License": "GPL (>= 2)",
  "LazyLoad": "yes",
  "RdMacros": "Rdpack",
  "URL": "https://geobosh.github.io/mixAR/ (doc),\nhttps://CRAN.R-project.org/package=mixAR/",
  "BugReports": "https://github.com/GeoBosh/mixAR/issues",
  "Collate": "raggedCoef.R raggedCoefS.R mixComp.R mixAR.R mixARcalc.R\nmixutil.R dist.R predict.R mix_se.R obs_info_matrix.R\nsamp_functions.R bayes_mixAR.R label_switch.R Choose_pk.R\nmarg_loglik.R mixSARfit.R mixARreg.R fit_mixARreg.R\nraggedCoefV.R mixVAR.R fit_mixVAR.R cond_loglikV.R mixVAR_sim.R\ntsdiag.R mixAR_diag.R devel.R em0.R emGaussian.R emgen.R\n00marmath.R exmodels.R mixARsim.R",
  "Encoding": "UTF-8",
  "Repository": "https://geobosh.r-universe.dev",
  "Date/Publication": "2025-12-08 17:35:24 UTC",
  "RemoteUrl": "https://github.com/geobosh/mixar",
  "RemoteRef": "HEAD",
  "RemoteSha": "a9f5cbeff175f6bbdd6410fabf4c548c4c2690cd",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-06 06:11:36 UTC",
    "User": "root"
  },
  "Author": "Georgi N. Boshnakov [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-2839-346X>),\nDavide Ravagli [aut] (ORCID: <https://orcid.org/0000-0001-7146-7685>)",
  "Maintainer": "Georgi N. Boshnakov <georgi.boshnakov@manchester.ac.uk>",
  "MD5sum": "31077656075aee0ae32e3fa11525b368",
  "_user": "geobosh",
  "_type": "src",
  "_file": "mixAR_0.22.8.9000.tar.gz",
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  "_sha256": "9993b69780e67bdeb9aed37d228969d815cc5b7ec985e6eaa8464c02ae46d98e",
  "_created": "2026-06-06T06:11:36.000Z",
  "_published": "2026-06-06T06:16:32.294Z",
  "_distro": "noble",
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  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/geobosh/mixar",
  "_commit": {
    "id": "a9f5cbeff175f6bbdd6410fabf4c548c4c2690cd",
    "author": "Georgi Boshnakov <georgi.boshnakov@gmail.com>",
    "committer": "Georgi Boshnakov <georgi.boshnakov@gmail.com>",
    "message": "remove redundant fields in DESCRIPTION\n",
    "time": 1765215324
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  "_maintainer": {
    "name": "Georgi N. Boshnakov",
    "email": "georgi.boshnakov@manchester.ac.uk",
    "orcid": "0000-0003-2839-346X"
  },
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  "_dependencies": [
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      "package": "R",
      "version": ">= 3.5",
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      "package": "methods",
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    {
      "package": "stats",
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    },
    {
      "package": "graphics",
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      "package": "utils",
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      "package": "stats4",
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    {
      "package": "BB",
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    {
      "package": "combinat",
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    },
    {
      "package": "timeDate",
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    {
      "package": "fGarch",
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      "package": "gbutils",
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    {
      "package": "MCMCpack",
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    {
      "package": "permute",
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    },
    {
      "package": "mvtnorm",
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      "package": "fma",
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    {
      "package": "testthat",
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    {
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  "_owner": "geobosh",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [
    {
      "week": "2025-50",
      "n": 2
    }
  ],
  "_tags": [],
  "_topics": [
    "asymmetric",
    "heteroskedasticity",
    "mixture-autoregressive",
    "student-t",
    "time-series"
  ],
  "_stars": 1,
  "_contributors": [
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      "user": "geobosh",
      "count": 44,
      "uuid": 22681858
    }
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    "type": "user",
    "name": "Georgi N. Boshnakov"
  },
  "_downloads": {
    "count": 288,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/mixAR"
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  "_devurl": "https://github.com/geobosh/mixar",
  "_pkgdown": "https://geobosh.github.io/mixAR/",
  "_searchresults": 8,
  "_rbuild": "4.6.0",
  "_assets": [
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    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/mixAR.html",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/readme.html",
    "extra/readme.md",
    "manual.pdf"
  ],
  "_homeurl": "https://github.com/geobosh/mixar",
  "_realowner": "geobosh",
  "_cranurl": true,
  "_releases": [
    {
      "version": "0.22.3",
      "date": "2020-06-22"
    },
    {
      "version": "0.22.4",
      "date": "2020-06-29"
    },
    {
      "version": "0.22.5",
      "date": "2021-01-04"
    },
    {
      "version": "0.22.6",
      "date": "2022-01-23"
    },
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      "version": "0.22.7",
      "date": "2022-05-03"
    },
    {
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      "date": "2023-12-19"
    },
    {
      "version": "0.22.9",
      "date": "2025-12-16"
    }
  ],
  "_exports": [
    "%of%",
    "adjustLengths",
    "b_show",
    "bayes_mixAR",
    "BIC_comp",
    "bx_dx",
    "Choose_pk",
    "companion_matrix",
    "cond_loglik",
    "cond_loglikS",
    "dist_norm",
    "distlist",
    "ed_nparam",
    "ed_parse",
    "ed_skeleton",
    "ed_src",
    "ed_stdnorm",
    "ed_stdt",
    "ed_stdt0",
    "ed_stdt1",
    "em_est_dist",
    "em_est_sigma",
    "em_rinit",
    "em_tau",
    "em_tau_safe",
    "err",
    "err_k",
    "est_templ",
    "etk2tau",
    "exampleModels",
    "fdist_stdnorm",
    "fdist_stdt",
    "fit_mixAR",
    "fit_mixARreg",
    "fit_mixVAR",
    "fn_stdt",
    "ft_stdt",
    "get_edist",
    "initialize",
    "inner",
    "isStable",
    "label_switch",
    "lastn",
    "lik_params",
    "lik_params_bounds",
    "make_fcond_lik",
    "marg_loglik",
    "mix_cdf",
    "mix_central_moment",
    "mix_ek",
    "mix_ekurtosis",
    "mix_hatk",
    "mix_kurtosis",
    "mix_location",
    "mix_moment",
    "mix_ncomp",
    "mix_pdf",
    "mix_qf",
    "mix_se",
    "mix_variance",
    "mixAny_sim",
    "mixAR",
    "mixAR_BIC",
    "mixAR_cond_probs",
    "mixAR_diag",
    "mixAR_permute",
    "mixAR_sim",
    "mixAR_switch",
    "mixARemFixedPoint",
    "mixARExperiment",
    "MixARGaussian",
    "mixARgen",
    "mixARgenemFixedPoint",
    "mixARnoise_sim",
    "mixARreg",
    "mixFilter",
    "mixgenMstep",
    "mixMstep",
    "mixSARfit",
    "mixSubsolve",
    "mixVAR_sim",
    "mixVARfit",
    "multiStep_dist",
    "noise_dist",
    "noise_moment",
    "noise_params",
    "noise_rand",
    "param_score_stdt",
    "parameters",
    "parameters<-",
    "permn_cols",
    "permuteArpar",
    "predict_coef",
    "rag_modify",
    "ragged2char",
    "ragged2vec",
    "raggedCoef",
    "raghat1",
    "randomArCoefficients",
    "randomMarParametersKernel",
    "randomMarResiduals",
    "row_lengths",
    "sampMuShift",
    "sampSigmaTau",
    "sampZpi",
    "set_noise_params",
    "show_diff",
    "simuExperiment",
    "stdnormabsmoment",
    "stdnormmoment",
    "stdtabsmoment",
    "stdtmoment",
    "tabsmoment",
    "tau2arcoef",
    "tau2probhat",
    "tauCorrelate",
    "tauetk2sigmahat",
    "test_unswitch",
    "tomarparambyComp",
    "tomarparambyType",
    "tsDesignMatrixExtended",
    "unswitch"
  ],
  "_datasets": [
    {
      "name": "PortfolioData1",
      "title": "Closing prices of four stocks",
      "object": "PortfolioData1",
      "file": "PortfolioData1.rda",
      "class": [
        "data.frame"
      ],
      "fields": [
        "DELL",
        "MSFT",
        "INTC",
        "IBM"
      ],
      "rows": 867,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "mixAR-package",
      "title": "Mixture Autoregressive Models",
      "concept": [
        "mixture autoregressive model",
        "MAR model",
        "TMAR model",
        "mixture autoregression",
        "non-gaussian time series",
        "asymmetry in time series",
        "multi-modality in time series"
      ],
      "topics": [
        "mixAR-package"
      ]
    },
    {
      "page": "bayes_mixAR",
      "title": "Bayesian sampling of mixture autoregressive models",
      "topics": [
        "bayes_mixAR"
      ]
    },
    {
      "page": "Choose_pk",
      "title": "Choose the autoregressive order of MixAR components",
      "topics": [
        "Choose_pk"
      ]
    },
    {
      "page": "cond_loglik",
      "title": "Log-likelihood of MixAR models",
      "topics": [
        "cond_loglik",
        "cond_loglikS"
      ]
    },
    {
      "page": "dist_norm",
      "title": "Functions for the standard normal distribution",
      "topics": [
        "dist_norm"
      ]
    },
    {
      "page": "em_est_dist",
      "title": "Optimise scale parameters in MixARgen models",
      "topics": [
        "em_est_dist"
      ]
    },
    {
      "page": "em_est_sigma",
      "title": "Update the scale parameters of MixAR models",
      "topics": [
        "em_est_sigma",
        "tauetk2sigmahat"
      ]
    },
    {
      "page": "em_rinit",
      "title": "Gaussian EM-step with random initialisation",
      "topics": [
        "em_rinit",
        "etk2tau"
      ]
    },
    {
      "page": "est_templ",
      "title": "Create estimation templates from MixAR model objects",
      "topics": [
        "est_templ"
      ]
    },
    {
      "page": "exampleModels",
      "title": "MixAR models for examples and testing",
      "topics": [
        "exampleModels",
        "moT_A",
        "moT_B",
        "moT_B2",
        "moT_B3",
        "moT_C1",
        "moT_C2",
        "moT_C3",
        "moWL",
        "moWLar",
        "moWLgen",
        "moWLprob",
        "moWLsigma",
        "moWLt3v",
        "moWLtf",
        "moWL_A",
        "moWL_B",
        "moWL_I",
        "moWL_II"
      ]
    },
    {
      "page": "fit_mixAR-methods",
      "title": "Fit mixture autoregressive models",
      "topics": [
        "fit_mixAR",
        "fit_mixAR,ANY,ANY,ANY-method",
        "fit_mixAR,ANY,MixAR,list-method",
        "fit_mixAR,ANY,MixAR,missing-method",
        "fit_mixAR,ANY,MixAR,MixAR-method",
        "fit_mixAR,ANY,MixAR,numeric-method",
        "fit_mixAR,ANY,MixARGaussian,MixAR-method",
        "fit_mixAR,ANY,numeric,missing-method",
        "fit_mixAR,ANY,numeric,numeric-method",
        "fit_mixAR-methods"
      ]
    },
    {
      "page": "fit_mixARreg-methods",
      "title": "Fit time series regression models with mixture autoregressive residuals",
      "topics": [
        "fit_mixARreg",
        "fit_mixARreg,ANY,ANY,missing,list-method",
        "fit_mixARreg,ANY,ANY,MixAR,list-method",
        "fit_mixARreg,ANY,data.frame,missing,list-method",
        "fit_mixARreg,ANY,data.frame,MixAR,missing-method",
        "fit_mixARreg,ANY,matrix,missing,list-method",
        "fit_mixARreg,ANY,matrix,MixAR,missing-method",
        "fit_mixARreg,ANY,numeric,missing,list-method",
        "fit_mixARreg,ANY,numeric,MixAR,missing-method",
        "fit_mixARreg-methods",
        "mixARreg"
      ]
    },
    {
      "page": "fit_mixVAR-methods",
      "title": "Fit mixture vector autoregressive models",
      "topics": [
        "fit_mixVAR",
        "fit_mixVAR,ANY,ANY-method",
        "fit_mixVAR,ANY,MixVAR-method",
        "fit_mixVAR-methods"
      ]
    },
    {
      "page": "fnoise",
      "title": "Generator functions for noise distributions",
      "topics": [
        "b_show",
        "distlist",
        "ed_nparam",
        "ed_parse",
        "ed_skeleton",
        "ed_src",
        "ed_stdnorm",
        "ed_stdt",
        "ed_stdt0",
        "ed_stdt1",
        "fdist_stdnorm",
        "fdist_stdt",
        "fnoise",
        "fn_stdt",
        "ft_stdt"
      ]
    },
    {
      "page": "get_edist-methods",
      "title": "Methods for function 'get_edist' in package 'mixAR'",
      "topics": [
        "get_edist,MixAR-method",
        "get_edist,MixARGaussian-method",
        "get_edist,MixARgen-method",
        "get_edist-methods"
      ]
    },
    {
      "page": "inner",
      "title": "Generalised inner product and methods for class '\"MixComp\"'",
      "topics": [
        "inner",
        "inner,ANY,ANY,ANY,ANY-method",
        "inner,MixComp,missing,missing,missing-method",
        "inner,MixComp,numeric,ANY,ANY-method",
        "inner,MixComp,numeric,ANY,missing-method",
        "inner,MixComp,numeric,missing,missing-method",
        "inner,numeric,MixComp,missing,missing-method",
        "inner-methods"
      ]
    },
    {
      "page": "isStable",
      "title": "Check if a MixAR model is stable",
      "topics": [
        "isStable"
      ]
    },
    {
      "page": "label_switch",
      "title": "A posteriori relabelling of a Markov chain",
      "topics": [
        "label_switch"
      ]
    },
    {
      "page": "lik_params",
      "title": "Vector of parameters of a MixAR model",
      "topics": [
        "lik_params",
        "lik_params,MixAR-method",
        "lik_params,MixARgen-method",
        "lik_params-methods"
      ]
    },
    {
      "page": "make_fcond_lik-methods",
      "title": "Create a function for computation of conditional likelihood",
      "topics": [
        "make_fcond_lik",
        "make_fcond_lik,MixAR,numeric-method",
        "make_fcond_lik-methods"
      ]
    },
    {
      "page": "marg_loglik",
      "title": "Calculate marginal loglikelihood at high density points of a MAR model.",
      "topics": [
        "marg_loglik"
      ]
    },
    {
      "page": "mix_ek",
      "title": "Function and methods to compute component residuals for MixAR models",
      "topics": [
        "mix_ek",
        "mix_ek,MixAR,numeric,missing,numeric,logical-method",
        "mix_ek,MixAR,numeric,missing,numeric,missing-method",
        "mix_ek,MixAR,numeric,numeric,missing,logical-method",
        "mix_ek,MixAR,numeric,numeric,missing,missing-method",
        "mix_ek-methods"
      ]
    },
    {
      "page": "mix_hatk",
      "title": "Compute component predictions for MixAR models",
      "topics": [
        "mix_hatk",
        "mix_hatk,MixAR,numeric,numeric,missing-method",
        "mix_hatk-methods"
      ]
    },
    {
      "page": "mix_moment",
      "title": "Conditional moments of MixAR models",
      "topics": [
        "mix_central_moment",
        "mix_ekurtosis",
        "mix_kurtosis",
        "mix_location",
        "mix_moment",
        "mix_variance"
      ]
    },
    {
      "page": "mix_ncomp-methods",
      "title": "Number of rows or columns of a MixComp object",
      "topics": [
        "mix_ncomp",
        "mix_ncomp,MixAR-method",
        "mix_ncomp,MixComp-method",
        "mix_ncomp-methods"
      ]
    },
    {
      "page": "mix_pdf-methods",
      "title": "Conditional pdf's and cdf's of MixAR models",
      "concept": [
        "MixAR",
        "prediction"
      ],
      "topics": [
        "mix_cdf",
        "mix_cdf,MixARGaussian,missing,missing,numeric-method",
        "mix_cdf,MixARGaussian,numeric,missing,numeric-method",
        "mix_cdf,MixARGaussian,numeric,numeric,missing-method",
        "mix_cdf,MixARgen,missing,missing,numeric-method",
        "mix_cdf,MixARgen,numeric,missing,numeric-method",
        "mix_cdf,MixARgen,numeric,numeric,missing-method",
        "mix_cdf-methods",
        "mix_pdf",
        "mix_pdf,MixARGaussian,missing,missing,numeric-method",
        "mix_pdf,MixARGaussian,numeric,missing,numeric-method",
        "mix_pdf,MixARGaussian,numeric,numeric,missing-method",
        "mix_pdf,MixARgen,missing,missing,numeric-method",
        "mix_pdf,MixARgen,numeric,missing,numeric-method",
        "mix_pdf,MixARgen,numeric,numeric,missing-method",
        "mix_pdf-methods"
      ]
    },
    {
      "page": "mix_qf-methods",
      "title": "Conditional quantile functions of MixAR models",
      "concept": [
        "MixAR",
        "prediction"
      ],
      "topics": [
        "mix_qf",
        "mix_qf,MixARGaussian,missing,missing,missing,numeric-method",
        "mix_qf,MixARGaussian,numeric,missing,missing,numeric-method",
        "mix_qf,MixARGaussian,numeric,numeric,numeric,missing-method",
        "mix_qf-methods"
      ]
    },
    {
      "page": "mix_se-methods",
      "title": "Compute standard errors of estimates of MixAR models",
      "topics": [
        "mix_se",
        "mix_se,ANY,list-method",
        "mix_se,ANY,MixAR-method",
        "mix_se,ANY,MixARGaussian-method",
        "mix_se-methods"
      ]
    },
    {
      "page": "mixAR_BIC",
      "title": "BIC based model selection for MixAR models",
      "topics": [
        "BIC_comp",
        "mixAR_BIC"
      ]
    },
    {
      "page": "mixAR_cond_probs",
      "title": "The E-step of the EM algorithm for MixAR models",
      "topics": [
        "mixAR_cond_probs"
      ]
    },
    {
      "page": "mixAR_diag",
      "title": "Diagnostic checks for mixture autoregressive models",
      "topics": [
        "mixAR_diag",
        "tsdiag",
        "tsdiag.MixAR"
      ]
    },
    {
      "page": "mixAR_sim",
      "title": "Simulate from MixAR models",
      "topics": [
        "mixAny_sim",
        "mixAR_sim"
      ]
    },
    {
      "page": "mixAR_switch",
      "title": "Relabel the components of a MixAR model",
      "topics": [
        "mixAR_permute",
        "mixAR_switch"
      ]
    },
    {
      "page": "MixAR-class",
      "title": "Class '\"MixAR\"' - mixture autoregressive models",
      "topics": [
        "MixAR-class"
      ]
    },
    {
      "page": "mixAR-methods",
      "title": "Create MixAR objects",
      "topics": [
        "mixAR",
        "mixAR,ANY-method",
        "mixAR,MixAR-method",
        "mixAR-methods"
      ]
    },
    {
      "page": "mixARemFixedPoint",
      "title": "EM estimation for mixture autoregressive models",
      "topics": [
        "mixARemFixedPoint",
        "mixARgenemFixedPoint"
      ]
    },
    {
      "page": "MixARGaussian-class",
      "title": "mixAR models with Gaussian noise components",
      "topics": [
        "MixARGaussian",
        "MixARGaussian-class"
      ]
    },
    {
      "page": "MixARgen-class",
      "title": "Class '\"MixARgen\"'",
      "topics": [
        "mixARgen",
        "MixARgen-class"
      ]
    },
    {
      "page": "mixARnoise_sim",
      "title": "Simulate white noise series from a list of functions and vector of regimes",
      "topics": [
        "mixARnoise_sim"
      ]
    },
    {
      "page": "MixComp-class",
      "title": "Class '\"MixComp\"' - manipulation of MixAR time series",
      "topics": [
        "*,character,MixComp-method",
        "*,function,MixComp-method",
        "*,MixComp,MixComp-method",
        "*,MixComp,numeric-method",
        "*,numeric,MixComp-method",
        "+,MixComp,numeric-method",
        "+,numeric,MixComp-method",
        "-,MixComp,missing-method",
        "-,MixComp,numeric-method",
        "-,numeric,MixComp-method",
        "/,MixComp,numeric-method",
        "/,numeric,MixComp-method",
        "dim,MixComp-method",
        "MixComp-class",
        "^,MixComp,numeric-method"
      ]
    },
    {
      "page": "mixFilter",
      "title": "Filter time series with MixAR filters",
      "topics": [
        "mixFilter",
        "mixFilter,ANY,ANY,ANY-method",
        "mixFilter,numeric,raggedCoef,numeric-method",
        "mixFilter-methods"
      ]
    },
    {
      "page": "mixgenMstep",
      "title": "M-step for models from class MixARgen",
      "topics": [
        "mixgenMstep"
      ]
    },
    {
      "page": "mixMstep",
      "title": "Internal functions for estimation of MixAR models with Gaussian components",
      "topics": [
        "mixMstep",
        "tau2arcoef",
        "tauCorrelate"
      ]
    },
    {
      "page": "mixSARfit",
      "title": "Fit mixture autoregressive models with seasonal AR parameters",
      "topics": [
        "mixSARfit"
      ]
    },
    {
      "page": "mixVAR_sim",
      "title": "Simulate from multivariate MixAR models",
      "topics": [
        "mixVAR_sim"
      ]
    },
    {
      "page": "MixVAR-class",
      "title": "Class '\"MixVAR\"' - mixture vector autoregressive models",
      "topics": [
        "MixVAR-class"
      ]
    },
    {
      "page": "mixVARfit",
      "title": "Fit mixture vector autoregressive models",
      "topics": [
        "mixVARfit"
      ]
    },
    {
      "page": "MixVARGaussian-class",
      "title": "MixVAR models with multivariate Gaussian noise components",
      "topics": [
        "MixVARGaussian",
        "MixVARGaussian-class"
      ]
    },
    {
      "page": "multiStep_dist-methods",
      "title": "Multi-step predictions for MixAR models",
      "topics": [
        "multiStep_dist",
        "multiStep_dist,MixAR,numeric,numeric,numeric-method",
        "multiStep_dist,MixARGaussian,numeric,missing,ANY-method",
        "multiStep_dist,MixARGaussian,numeric,missing,missing-method",
        "multiStep_dist-methods"
      ]
    },
    {
      "page": "noise_dist",
      "title": "Internal mixAR functions",
      "topics": [
        "get_edist",
        "noise_dist",
        "noise_params",
        "noise_rand",
        "set_noise_params"
      ]
    },
    {
      "page": "noise_dist-methods",
      "title": "Methods for function 'noise_dist' in package 'mixAR'",
      "topics": [
        "noise_dist,MixAR-method",
        "noise_dist,MixARGaussian-method",
        "noise_dist,MixARgen-method",
        "noise_dist-methods"
      ]
    },
    {
      "page": "noise_params-methods",
      "title": "Methods for function 'noise_params' in package 'mixAR'",
      "topics": [
        "noise_params,MixAR-method",
        "noise_params,MixARgen-method",
        "noise_params-methods"
      ]
    },
    {
      "page": "noise_rand-methods",
      "title": "Methods for function 'noise_rand' in package 'mixAR'",
      "topics": [
        "noise_rand,MixAR-method",
        "noise_rand,MixARGaussian-method",
        "noise_rand,MixARgen-method",
        "noise_rand-methods"
      ]
    },
    {
      "page": "parameters",
      "title": "Set or extract the parameters of MixAR objects",
      "topics": [
        "parameters",
        "parameters,ANY-method",
        "parameters,MixAR-method",
        "parameters-methods",
        "parameters<-",
        "parameters<-,ANY-method",
        "parameters<-,MixAR-method",
        "parameters<--methods",
        "set_parameters",
        "set_parameters,ANY-method",
        "set_parameters,MixAR-method",
        "set_parameters-methods"
      ]
    },
    {
      "page": "percent_of",
      "title": "Infix operator to apply functions to matrix-like objects",
      "topics": [
        "%of%",
        "%of%,ANY,ANY-method",
        "%of%,character,MixComp-method",
        "%of%,function,MixComp-method",
        "%of%,list,MixComp-method",
        "%of%-methods",
        "percent_of"
      ]
    },
    {
      "page": "permn_cols",
      "title": "All permutations of the columns of a matrix",
      "topics": [
        "permn_cols"
      ]
    },
    {
      "page": "PortfolioData1",
      "title": "Closing prices of four stocks",
      "topics": [
        "PortfolioData1"
      ]
    },
    {
      "page": "predict_coef",
      "title": "Exact predictive parameters for multi-step MixAR prediction",
      "topics": [
        "predict_coef"
      ]
    },
    {
      "page": "ragged",
      "title": "Small utilities for ragged objects",
      "topics": [
        "ragged2vec",
        "rag_modify"
      ]
    },
    {
      "page": "raggedCoef-class",
      "title": "Class '\"raggedCoef\"' - ragged list objects",
      "topics": [
        "anyNA,raggedCoef-method",
        "dim,raggedCoef-method",
        "length,raggedCoef-method",
        "raggedCoef",
        "raggedCoef-class",
        "[,raggedCoef,missing,missing,ANY-method",
        "[,raggedCoef,missing,numeric,ANY-method",
        "[,raggedCoef,numeric,missing,ANY-method",
        "[,raggedCoef,numeric,numeric,ANY-method",
        "[-methods",
        "[<-,raggedCoef,ANY,ANY,numeric-method",
        "[<-,raggedCoef,ANY,missing,list-method",
        "[<-,raggedCoef,ANY,missing,matrix-method",
        "[<-,raggedCoef,ANY,missing,numeric-method",
        "[<-,raggedCoef,missing,missing,ANY-method",
        "[<-,raggedCoef,missing,missing,list-method",
        "[<-,raggedCoef,missing,missing,matrix-method",
        "[<-,raggedCoef,missing,missing,numeric-method",
        "[<-,raggedCoef,numeric,missing,ANY-method",
        "[<-,raggedCoef,numeric,numeric,ANY-method",
        "[[,raggedCoef,ANY,ANY-method",
        "[[,raggedCoef,ANY,missing-method",
        "[[-methods",
        "[[<-,raggedCoef,ANY,ANY,numeric-method",
        "[[<-,raggedCoef,ANY,missing,numeric-method",
        "[[<--methods"
      ]
    },
    {
      "page": "raggedCoefS-class",
      "title": "Class '\"raggedCoefS\"' - ragged list",
      "topics": [
        "raggedCoefS",
        "raggedCoefS-class",
        "[,raggedCoefS,missing,missing,ANY-method",
        "[,raggedCoefS,missing,numeric,ANY-method",
        "[,raggedCoefS,numeric,missing,ANY-method",
        "[,raggedCoefS,numeric,numeric,ANY-method",
        "[[,raggedCoefS,ANY,ANY-method",
        "[[,raggedCoefS,ANY,missing-method",
        "[[<-,raggedCoefS,ANY,ANY,numeric-method",
        "[[<-,raggedCoefS,ANY,missing,list-method"
      ]
    },
    {
      "page": "raggedCoefV-class",
      "title": "Class '\"raggedCoefV\"' - ragged list",
      "topics": [
        "raggedCoefV",
        "raggedCoefV-class",
        "[,raggedCoefV,missing,ANY,ANY-method",
        "[,raggedCoefV,missing,numeric,ANY-method",
        "[,raggedCoefV,numeric,ANY,ANY-method",
        "[,raggedCoefV,numeric,ANY-method",
        "[,raggedCoefV,numeric,missing,ANY-method",
        "[,raggedCoefV,numeric,numeric,ANY-method",
        "[[,raggedCoefV,missing,ANY-method",
        "[[,raggedCoefV,numeric,ANY-method"
      ]
    },
    {
      "page": "raghat1",
      "title": "Filter a time series with options to shift and scale",
      "topics": [
        "raghat1"
      ]
    },
    {
      "page": "randomArCoefficients",
      "title": "Random initial values for MixAR estimation",
      "topics": [
        "randomArCoefficients",
        "randomMarParametersKernel",
        "randomMarResiduals",
        "tsDesignMatrixExtended"
      ]
    },
    {
      "page": "row_length-methods",
      "title": "Methods for function 'row_lengths' in package 'mixAR'",
      "topics": [
        "row_lengths",
        "row_lengths,ANY-method",
        "row_lengths,MixAR-method",
        "row_lengths,raggedCoef-method",
        "row_lengths-methods"
      ]
    },
    {
      "page": "sampZpi",
      "title": "Sampling functions for Bayesian analysis of mixture autoregressive models",
      "topics": [
        "sampMuShift",
        "sampSigmaTau",
        "sampZpi"
      ]
    },
    {
      "page": "show_diff",
      "title": "Show differences between two models",
      "topics": [
        "show_diff",
        "show_diff,MixAR,MixAR-method",
        "show_diff,MixARGaussian,MixARgen-method",
        "show_diff,MixARgen,MixARGaussian-method",
        "show_diff,MixARgen,MixARgen-method",
        "show_diff-methods"
      ]
    },
    {
      "page": "simuExperiment",
      "title": "Perform simulation experiments",
      "topics": [
        "simuExperiment"
      ]
    },
    {
      "page": "stdnormmoment",
      "title": "Compute moments and absolute moments of standardised-t and normal distributions",
      "topics": [
        "stdnormabsmoment",
        "stdnormmoment",
        "stdtabsmoment",
        "stdtmoment",
        "tabsmoment"
      ]
    },
    {
      "page": "tomarparambyComp",
      "title": "Translations of my old MixAR Mathematica functions",
      "topics": [
        "permuteArpar",
        "tomarparambyComp",
        "tomarparambyType"
      ]
    }
  ],
  "_readme": "https://github.com/geobosh/mixar/raw/HEAD/README.md",
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    "fGarch",
    "gbutils",
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    "lattice",
    "MASS",
    "Matrix",
    "MatrixModels",
    "mcmc",
    "MCMCpack",
    "mvtnorm",
    "permute",
    "proxy",
    "quadprog",
    "quantreg",
    "rbibutils",
    "Rdpack",
    "SparseM",
    "spatial",
    "stabledist",
    "survival",
    "timeDate",
    "timeSeries"
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  "_score": 2.6989700043360187,
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  "_nocasepkg": "mixar",
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