{
  "_id": "6a1e10801d7bb097a0a5e701",
  "Package": "RobMixReg",
  "Type": "Package",
  "Title": "Robust Mixture Regression",
  "Version": "1.1.3",
  "Date": "2026-06-01",
  "Authors@R": "c(person(\"Sha\", \"Cao\", email = \"shacao@iu.edu\", role = c(\"aut\", \"cph\",\"ths\")),\nperson(\"Wennan\", \"Chang\", email = \"changwn.nku@gmail.com\", role = c(\"aut\", \"cre\")),\nperson(\"Chi\", \"Zhang\", email = \"czhang87@iu.edu\", role = c(\"aut\", \"ctb\",\"ths\"))\n)",
  "Author": "Sha Cao [aut, cph, ths], Wennan Chang [aut, cre], Chi Zhang\n[aut, ctb, ths]",
  "Maintainer": "Wennan Chang <changwn.nku@gmail.com>",
  "Description": "Finite mixture models are a popular technique for\nmodelling unobserved heterogeneity or to approximate general\ndistribution functions in a semi-parametric way. They are used\nin a lot of different areas such as astronomy, biology,\neconomics, marketing or medicine. This package is the\nimplementation of popular robust mixture regression methods\nbased on different algorithms including: fleximix, finite\nmixture models and latent class regression; CTLERob,\ncomponent-wise adaptive trimming likelihood estimation; mixbi,\nbi-square estimation; mixL, Laplacian distribution; mixt,\nt-distribution; TLE, trimmed likelihood estimation. The\nimplemented algorithms includes: CTLERob stands for\nComponent-wise adaptive Trimming Likelihood Estimation based\nmixture regression; mixbi stands for mixture regression based\non bi-square estimation; mixLstands for mixture regression\nbased on Laplacian distribution; TLE stands for Trimmed\nLikelihood Estimation based mixture regression. For more detail\nof the algorithms, please refer to below references. Reference:\nChun Yu, Weixin Yao, Kun Chen (2017) <doi:10.1002/cjs.11310>.\nNeyKov N, Filzmoser P, Dimova R et al. (2007)\n<doi:10.1016/j.csda.2006.12.024>. Bai X, Yao W. Boyer JE (2012)\n<doi:10.1016/j.csda.2012.01.016>. Wennan Chang, Xinyu Zhou,\nYong Zang, Chi Zhang, Sha Cao (2020)\n<doi:10.48550/arXiv.2005.11599>.",
  "License": "GPL",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "RoxygenNote": "7.3.2",
  "URL": "https://changwn.github.io/RobMixReg/",
  "BugReports": "https://github.com/changwn/RobMixReg/issues",
  "Repository": "https://changwn.r-universe.dev",
  "Date/Publication": "2026-06-01 22:43:34 UTC",
  "RemoteUrl": "https://github.com/changwn/robmixreg",
  "RemoteRef": "HEAD",
  "RemoteSha": "97c9b4954d135eea16b96f20dc08c77fae5334bb",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-01 23:03:37 UTC",
    "User": "root"
  },
  "MD5sum": "7600d5fa700036e23d0a185f09cd59ec",
  "_user": "changwn",
  "_type": "src",
  "_file": "RobMixReg_1.1.3.tar.gz",
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  "_filesize": 2468437,
  "_sha256": "ee8e2aab50c84fd86c78a35bae9cdfb6f4507d1ee3d82299f3ffbbbcc4848046",
  "_created": "2026-06-01T23:03:37.000Z",
  "_published": "2026-06-01T23:06:40.020Z",
  "_distro": "noble",
  "_jobs": [
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  "_buildurl": "https://github.com/r-universe/changwn/actions/runs/26787243151",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/changwn/robmixreg",
  "_commit": {
    "id": "97c9b4954d135eea16b96f20dc08c77fae5334bb",
    "author": "WC <changwn.nku@gmail.com>",
    "committer": "WC <changwn.nku@gmail.com>",
    "message": "Remove Rcheck folder from repo and ignore it\n",
    "time": 1780353814
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  "_maintainer": {
    "name": "Wennan Chang",
    "email": "changwn.nku@gmail.com",
    "login": "changwn",
    "description": "Ph.D. working on computation biology and mathmatical modeling for biomedical data analysis.",
    "uuid": 18462843
  },
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 3.5.0",
      "role": "Depends"
    },
    {
      "package": "flexmix",
      "role": "Imports"
    },
    {
      "package": "robustbase",
      "role": "Imports"
    },
    {
      "package": "gtools",
      "role": "Imports"
    },
    {
      "package": "MASS",
      "role": "Imports"
    },
    {
      "package": "methods",
      "role": "Imports"
    },
    {
      "package": "robust",
      "role": "Imports"
    },
    {
      "package": "lars",
      "role": "Imports"
    },
    {
      "package": "dplyr",
      "role": "Imports"
    },
    {
      "package": "rlang",
      "role": "Imports"
    },
    {
      "package": "scales",
      "role": "Imports"
    },
    {
      "package": "gplots",
      "role": "Imports"
    },
    {
      "package": "grDevices",
      "role": "Imports"
    },
    {
      "package": "graphics",
      "role": "Imports"
    },
    {
      "package": "RColorBrewer",
      "role": "Imports"
    },
    {
      "package": "stats",
      "role": "Imports"
    }
  ],
  "_owner": "changwn",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [
    {
      "week": "2026-23",
      "n": 5
    }
  ],
  "_tags": [],
  "_stars": 0,
  "_contributors": [
    {
      "user": "changwn",
      "count": 124,
      "uuid": 18462843
    }
  ],
  "_userbio": {
    "uuid": 18462843,
    "type": "user",
    "name": "Wennan Chang",
    "description": "Ph.D. working on computation biology and mathmatical modeling for biomedical data analysis."
  },
  "_downloads": {
    "count": 152,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/RobMixReg"
  },
  "_devurl": "https://github.com/changwn/robmixreg",
  "_pkgdown": "https://changwn.github.io/RobMixReg/",
  "_rbuild": "4.6.0",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/readme.html",
    "extra/readme.md",
    "extra/RobMixReg.html",
    "manual.pdf"
  ],
  "_homeurl": "https://github.com/changwn/robmixreg",
  "_realowner": "changwn",
  "_cranurl": true,
  "_releases": [
    {
      "version": "0.1.0",
      "date": "2020-03-25"
    },
    {
      "version": "0.2.0",
      "date": "2020-05-11"
    },
    {
      "version": "0.2.1",
      "date": "2020-05-26"
    },
    {
      "version": "1.0.0",
      "date": "2020-06-08"
    },
    {
      "version": "1.1.0",
      "date": "2020-08-05"
    }
  ],
  "_exports": [
    "biscalew",
    "bisquare",
    "blockMap",
    "calcobj_i",
    "compPlot",
    "Compute_Rbase_SVD",
    "CSMR",
    "CSMR_one",
    "CSMR_predict",
    "CSMR_train",
    "CTLERob",
    "denLp",
    "DeOut",
    "dmnorm",
    "estimClustPar_i",
    "findClustAssig_i",
    "flexmix_2",
    "getini",
    "InitClusters_i",
    "lars.lsa",
    "logLik_mixtureReg",
    "lsa",
    "mixlinrb_bi",
    "mixlinrb_bione",
    "mixLp",
    "mixLp_one",
    "mixtureReg",
    "MLM",
    "MLM_bic",
    "MLM_cv",
    "orderedLines",
    "plot_CTLE",
    "plot_mixtureReg",
    "plot_mixtureRegList",
    "Rec_Lm",
    "restr.diffax_i1",
    "restr.diffax_i2",
    "restr2_eigenv",
    "rmr",
    "simu_data_sparse",
    "simu_func",
    "simu_low",
    "ssclmat",
    "TLE",
    "TreatSingularity",
    "trim.cwm"
  ],
  "_datasets": [
    {
      "name": "CCLE_data",
      "title": "RobMixReg package built-in CCLE data.",
      "object": "CCLE_data",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "colon_data",
      "title": "RobMixReg package built-in Colon cancer data.",
      "object": "colon_data",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "gaussData",
      "title": "RobMixReg package built-in gaussian example data.",
      "object": "gaussData",
      "class": [
        "data.frame"
      ],
      "fields": [
        "x",
        "y",
        "c"
      ],
      "rows": 100,
      "table": true,
      "tojson": true
    },
    {
      "name": "simuData",
      "title": "RobMixReg package built-in simulated example data.",
      "object": "simuData",
      "class": [
        "data.frame"
      ],
      "fields": [
        "X1",
        "X2",
        "y",
        "c",
        "outlier"
      ],
      "rows": 500,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "biscalew",
      "title": "biscalew :Robust M-estimates for scale.",
      "topics": [
        "biscalew"
      ]
    },
    {
      "page": "bisquare",
      "title": "bisquare : Robust estimates for mean.",
      "topics": [
        "bisquare"
      ]
    },
    {
      "page": "blockMap",
      "title": "Plot the coefficient matrix.",
      "topics": [
        "blockMap"
      ]
    },
    {
      "page": "calcobj_i",
      "title": "calcobj_i: it calculates the objective function",
      "topics": [
        "calcobj_i"
      ]
    },
    {
      "page": "CCLE_data",
      "title": "RobMixReg package built-in CCLE data.",
      "topics": [
        "CCLE_data"
      ]
    },
    {
      "page": "colon_data",
      "title": "RobMixReg package built-in Colon cancer data.",
      "topics": [
        "colon_data"
      ]
    },
    {
      "page": "compPlot",
      "title": "The plot wrapper function.",
      "topics": [
        "compPlot"
      ]
    },
    {
      "page": "Compute_Rbase_SVD",
      "title": "Compute the row space using SVD.",
      "topics": [
        "Compute_Rbase_SVD"
      ]
    },
    {
      "page": "CSMR",
      "title": "The main function of the RBSL algorithm.",
      "topics": [
        "CSMR"
      ]
    },
    {
      "page": "CSMR_one",
      "title": "Perform the RBSL algorithm one times.",
      "topics": [
        "CSMR_one"
      ]
    },
    {
      "page": "CSMR_predict",
      "title": "The predict function of the CSMR algorithm.",
      "topics": [
        "CSMR_predict"
      ]
    },
    {
      "page": "CSMR_train",
      "title": "The train function of the CSMR algorithm.",
      "topics": [
        "CSMR_train"
      ]
    },
    {
      "page": "CTLERob-methods",
      "title": "CTLERob: Robust mixture regression based on component-wise adaptive trimming likelihood estimation.",
      "topics": [
        "CTLERob",
        "CTLERob,formula,ANY,ANY,numeric,ANY-method",
        "CTLERob,formula,ANY,ANY,numeric-method"
      ]
    },
    {
      "page": "denLp",
      "title": "denLp : Density function for Laplace distribution.",
      "topics": [
        "denLp"
      ]
    },
    {
      "page": "DeOut",
      "title": "DeOut : Detect outlier observations.",
      "topics": [
        "DeOut"
      ]
    },
    {
      "page": "dmnorm",
      "title": "dmnorm: multivariate normal density function",
      "topics": [
        "dmnorm"
      ]
    },
    {
      "page": "estimClustPar_i",
      "title": "estimClustPar_i: see original CWM method",
      "topics": [
        "estimClustPar_i"
      ]
    },
    {
      "page": "findClustAssig_i",
      "title": "findClustAssig_i: it obtains the assigment corresponding to each point to the K populations and the set of trimmed points",
      "topics": [
        "findClustAssig_i"
      ]
    },
    {
      "page": "flexmix_2",
      "title": "flexmix_2: Multiple runs of MLE based mixture regression to stabilize the output.",
      "topics": [
        "flexmix_2"
      ]
    },
    {
      "page": "gaussData",
      "title": "RobMixReg package built-in gaussian example data.",
      "topics": [
        "gaussData"
      ]
    },
    {
      "page": "getini",
      "title": "getini: see original CWM method",
      "topics": [
        "getini"
      ]
    },
    {
      "page": "InitClusters_i",
      "title": "InitClusters_i: see original CWM method",
      "topics": [
        "InitClusters_i"
      ]
    },
    {
      "page": "lars.lsa",
      "title": "lars variant for LSA.",
      "topics": [
        "lars.lsa"
      ]
    },
    {
      "page": "logLik_mixtureReg",
      "title": "Obtain Log-likelihood from a mixtureReg Object",
      "topics": [
        "logLik_mixtureReg"
      ]
    },
    {
      "page": "lsa",
      "title": "Least square approximation. This version Oct 19, 2006.",
      "topics": [
        "lsa"
      ]
    },
    {
      "page": "mixlinrb_bi-methods",
      "title": "mixlinrb_bi: mixlinrb_bione estimates the mixture regression parameters robustly using bisquare function based on multiply initial value.",
      "topics": [
        "mixlinrb_bi",
        "mixlinrb_bi,formula,ANY,numeric,numeric-method"
      ]
    },
    {
      "page": "mixlinrb_bione",
      "title": "mixlinrb_bione : mixlinrb_bione estimates the mixture regression parameters robustly using bisquare function based on one initial value.",
      "topics": [
        "mixlinrb_bione"
      ]
    },
    {
      "page": "mixLp-methods",
      "title": "mixLp : mixLp_one estimates the mixture regression parameters robustly using Laplace distribution based on multiply initial value..",
      "topics": [
        "CTLE,formula,ANY,numeric,numeric-method",
        "mixLp",
        "mixLp,formula,ANY,numeric,numeric-method"
      ]
    },
    {
      "page": "mixLp_one",
      "title": "mixLp_one : mixLp_one estimates the mixture regression parameters robustly using Laplace distribution based on one initial value.",
      "topics": [
        "mixLp_one"
      ]
    },
    {
      "page": "mixtureReg",
      "title": "Function to Fit Mixture of Regressions",
      "topics": [
        "mixtureReg"
      ]
    },
    {
      "page": "MLM",
      "title": "The main function of mining the latent relationship among variables.",
      "topics": [
        "MLM"
      ]
    },
    {
      "page": "MLM_bic",
      "title": "Model selection function for low dimension data.",
      "topics": [
        "MLM_bic"
      ]
    },
    {
      "page": "MLM_cv",
      "title": "Cross validation (fold-5) function for high dimension data.",
      "topics": [
        "MLM_cv"
      ]
    },
    {
      "page": "orderedLines",
      "title": "Sort by X Coordinates and Add Line to a Plot",
      "topics": [
        "orderedLines"
      ]
    },
    {
      "page": "plot_CTLE-methods",
      "title": "plot_CTLE: Plot the mixture/single regression line(s) in a simply function.",
      "topics": [
        "CTLERob,formula,ANY,numeric,ANY",
        "plot_CTLE",
        "plot_CTLE,formula,ANY,numeric-method"
      ]
    },
    {
      "page": "plot_mixtureReg",
      "title": "Plot Fit and Mixing Probability of a mixtureReg Object",
      "topics": [
        "plot_mixtureReg"
      ]
    },
    {
      "page": "plot_mixtureRegList",
      "title": "Plot a List of mixtureReg Objects",
      "topics": [
        "plot_mixtureRegList"
      ]
    },
    {
      "page": "Rec_Lm",
      "title": "Adaptive lasso.",
      "topics": [
        "Rec_Lm"
      ]
    },
    {
      "page": "restr.diffax_i1",
      "title": "restr.diffax_i1: see original CWM method",
      "topics": [
        "restr.diffax_i1"
      ]
    },
    {
      "page": "restr.diffax_i2",
      "title": "restr.diffax_i2: see original CWM method",
      "topics": [
        "restr.diffax_i2"
      ]
    },
    {
      "page": "restr2_eigenv",
      "title": "restr2_eigenv: see original CWM method",
      "topics": [
        "restr2_eigenv"
      ]
    },
    {
      "page": "rmr",
      "title": "The main function of Robust Mixture Regression using five methods.",
      "topics": [
        "rmr"
      ]
    },
    {
      "page": "RobMixReg-class",
      "title": "Class RobMixReg.",
      "topics": [
        "RobMixReg-class"
      ]
    },
    {
      "page": "simu_data_sparse",
      "title": "Simulate high dimension data for RBSL algorithm validation.",
      "topics": [
        "simu_data_sparse"
      ]
    },
    {
      "page": "simu_func",
      "title": "The simulation function for low/high dimensional space.",
      "topics": [
        "simu_func"
      ]
    },
    {
      "page": "simu_low",
      "title": "The simulation function for low dimensional space.",
      "topics": [
        "simu_low"
      ]
    },
    {
      "page": "simuData",
      "title": "RobMixReg package built-in simulated example data.",
      "topics": [
        "simuData"
      ]
    },
    {
      "page": "ssclmat",
      "title": "ssclmat: see original CWM method",
      "topics": [
        "ssclmat"
      ]
    },
    {
      "page": "TLE-methods",
      "title": "TLE: robust mixture regression based on trimmed likelihood estimation.",
      "topics": [
        "CTLE,formula,ANY,numeric,numeric,numeric-method",
        "TLE",
        "TLE,formula,ANY,numeric,numeric,numeric-method"
      ]
    },
    {
      "page": "TreatSingularity",
      "title": "TreatSingularity: see original CWM method",
      "topics": [
        "TreatSingularity"
      ]
    },
    {
      "page": "trim.cwm",
      "title": "trim.cwm: main function",
      "topics": [
        "trim.cwm"
      ]
    }
  ],
  "_readme": "https://github.com/changwn/robmixreg/raw/HEAD/README.md",
  "_rundeps": [
    "bitops",
    "caTools",
    "cli",
    "DEoptimR",
    "dplyr",
    "farver",
    "fit.models",
    "flexmix",
    "generics",
    "glue",
    "gplots",
    "gtools",
    "KernSmooth",
    "labeling",
    "lars",
    "lattice",
    "lifecycle",
    "magrittr",
    "MASS",
    "modeltools",
    "mvtnorm",
    "nnet",
    "pcaPP",
    "pillar",
    "pkgconfig",
    "R6",
    "RColorBrewer",
    "rlang",
    "robust",
    "robustbase",
    "rrcov",
    "scales",
    "tibble",
    "tidyselect",
    "utf8",
    "vctrs",
    "viridisLite",
    "withr"
  ],
  "_score": 2.6989700043360187,
  "_indexed": true,
  "_nocasepkg": "robmixreg",
  "_universes": [
    "changwn"
  ],
  "_previous": "1.1.2",
  "_binaries": [
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