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  "Version": "0.1-4",
  "Date": "2024-10-16",
  "Title": "Mixture fMRI Clustering Analysis",
  "Authors@R": "c(person(\"Wei-Chen\", \"Chen\", role = c(\"aut\", \"cre\"), email =\n\"wccsnow@gmail.com\"),\nperson(\"Ranjan\", \"Maitra\", role = \"aut\", email = \"maitra@iastate.edu\"),\nperson(\"Dan\", \"Nettleton\", role = c(\"aut\", \"ctb\")),\nperson(\"Pierre\", \"Lafaye De Micheaux\", role = c(\"aut\", \"ctb\"),\ncomment = \"Threshold functions from AnalyzeFMRI\"),\nperson(\"Jonathan L\", \"Marchini\", role = c(\"aut\", \"ctb\"),\ncomment = \"Threshold functions from AnalyzeFMRI\"))",
  "LazyLoad": "yes",
  "LazyData": "yes",
  "Description": "Utilizing model-based clustering (unsupervised) for\nfunctional magnetic resonance imaging (fMRI) data. The\ndeveloped methods (Chen and Maitra (2023)\n<doi:10.1002/hbm.26425>) include 2D and 3D clustering analyses\n(for p-values with voxel locations) and segmentation analyses\n(for p-values alone) for fMRI data where p-values indicate\nsignificant level of activation responding to stimulate of\ninteresting. The analyses are mainly identifying active\nvoxel/signal associated with normal brain behaviors. Analysis\npipelines (R scripts) utilizing this package (see examples in\n'inst/workflow/') is also implemented with high performance\ntechniques.",
  "License": "Mozilla Public License 2.0",
  "BugReports": "https://github.com/snoweye/MixfMRI/issues",
  "URL": "https://github.com/snoweye/MixfMRI",
  "NeedsCompilation": "yes",
  "Maintainer": "Wei-Chen Chen <wccsnow@gmail.com>",
  "Config/pak/sysreqs": "libfftw3-dev",
  "Repository": "https://snoweye.r-universe.dev",
  "Date/Publication": "2024-10-17 01:36:41 UTC",
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    "User": "root"
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  "Author": "Wei-Chen Chen [aut, cre],\nRanjan Maitra [aut],\nDan Nettleton [aut, ctb],\nPierre Lafaye De Micheaux [aut, ctb] (Threshold functions from\nAnalyzeFMRI),\nJonathan L Marchini [aut, ctb] (Threshold functions from AnalyzeFMRI)",
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  "_created": "2026-07-09T05:43:49.000Z",
  "_published": "2026-07-09T05:54:04.408Z",
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      "package": "R",
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      "role": "Imports"
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      "package": "Matrix",
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      "package": "RColorBrewer",
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    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/MixfMRI"
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  "_assets": [
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    "extra/citation.html",
    "extra/citation.json",
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    "extra/contents.json",
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    "manual.pdf"
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      "date": "2018-04-26"
    },
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      "date": "2021-02-13"
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    "apecma.step.gbd",
    "cba.cor",
    "cba.cor.2d",
    "cba.cor.3d",
    "cluster.threshold",
    "cov.logit.ETA",
    "cov.logit.z",
    "cov.param",
    "cov.post.z",
    "dmixpval",
    "dpval",
    "EC.3D",
    "em.step.gbd",
    "fclust",
    "fdr.bh.p1",
    "fdr.bh.p2",
    "gcv.smooth2d",
    "gendataset",
    "initial.em.gbd",
    "initial.RndEM.gbd",
    "lmt.I",
    "lmt.pv",
    "logor.stat",
    "lrt",
    "lrt.betaab",
    "lrt.betamean",
    "lrt2",
    "my.alpha.append",
    "my.Reds",
    "my.YlGnBu",
    "my.YlOrRd",
    "plotfclust",
    "plotfclustpv",
    "plotpv",
    "plotpvlegend",
    "post.prob",
    "qvalue",
    "set.global",
    "summarized.overlap",
    "Threshold.Bonferroni",
    "Threshold.FDR",
    "Threshold.RF"
  ],
  "_datasets": [
    {
      "name": ".FC.CT",
      "title": "Sets of controls in MixfMRI",
      "object": "control",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": ".MixfMRIEnv",
      "title": "All General Internal Functions and Datasets",
      "object": "envir",
      "class": [
        "environment"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "pstats",
      "title": "Example datasets in MixfMRI",
      "object": "pstats",
      "class": [
        "array"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "pval.2d.complex",
      "title": "Example datasets in MixfMRI",
      "object": "pval",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [],
      "rows": 128,
      "table": true,
      "tojson": true
    },
    {
      "name": "pval.2d.mag",
      "title": "Example datasets in MixfMRI",
      "object": "pval",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [],
      "rows": 128,
      "table": true,
      "tojson": true
    },
    {
      "name": "shepp0fMRI",
      "title": "Example datasets in MixfMRI",
      "object": "2dphant",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [],
      "rows": 256,
      "table": true,
      "tojson": true
    },
    {
      "name": "shepp1fMRI",
      "title": "Example datasets in MixfMRI",
      "object": "2dphant",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [],
      "rows": 256,
      "table": true,
      "tojson": true
    },
    {
      "name": "shepp2fMRI",
      "title": "Example datasets in MixfMRI",
      "object": "2dphant",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [],
      "rows": 256,
      "table": true,
      "tojson": true
    },
    {
      "name": "sheppAnat",
      "title": "Example datasets in MixfMRI",
      "object": "2dphant",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [],
      "rows": 256,
      "table": true,
      "tojson": true
    },
    {
      "name": "toy1",
      "title": "Example datasets in MixfMRI",
      "object": "toy",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "toy2",
      "title": "Example datasets in MixfMRI",
      "object": "toy",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "00_MixfMRI-package",
      "title": "fMRI Clustering Analysis",
      "topics": [
        "MixfMRI-package",
        "MixfMRI"
      ]
    },
    {
      "page": "b2_algorithm",
      "title": "Main algorithms implemented in fclust",
      "topics": [
        "apecma.step.gbd",
        "ecm.step.gbd",
        "em.step.gbd"
      ]
    },
    {
      "page": "y5_cluster.threshold",
      "title": "Cluster threshold an array.",
      "topics": [
        "cluster.threshold",
        "cluster_mass"
      ]
    },
    {
      "page": "u2_qvalue",
      "title": "Q-values using Benjamini and Hochberg (1995)",
      "topics": [
        "qvalue"
      ]
    },
    {
      "page": "f4_logor_stat",
      "title": "Compute Statistics for Log Odds Ratio of Posterior Probability",
      "topics": [
        "logor.stat"
      ]
    },
    {
      "page": "f3_post_I",
      "title": "Covariance Matrices",
      "topics": [
        "cov.logit.z",
        "cov.param",
        "cov.post.z",
        "post.prob"
      ]
    },
    {
      "page": "f2_logit_ETA",
      "title": "Covariance Matrices of Logit ETA",
      "topics": [
        "cov.logit.ETA"
      ]
    },
    {
      "page": "e2_density",
      "title": "Density function of p-values",
      "topics": [
        "dmixpval",
        "dpval"
      ]
    },
    {
      "page": "y3_EC.3D",
      "title": "Expected Euler Characteristic for a 3D Random Field",
      "topics": [
        "EC.3D"
      ]
    },
    {
      "page": "22_d_data",
      "title": "Example datasets in MixfMRI",
      "topics": [
        "pstats",
        "pval.2d.complex",
        "pval.2d.mag",
        "shepp0fMRI",
        "shepp1fMRI",
        "shepp2fMRI",
        "sheppAnat",
        "toy1",
        "toy2"
      ]
    },
    {
      "page": "u3_fdr_ss",
      "title": "False Discovery Rates for Spatial Signals using Benjamini and Heller (2007)",
      "topics": [
        "fdr.bh.p1",
        "fdr.bh.p2"
      ]
    },
    {
      "page": "u4_cba_cor",
      "title": "Generalized Cluster-Based Analysis (CBA) Method",
      "topics": [
        "cba.cor",
        "cba.cor.2d",
        "cba.cor.3d"
      ]
    },
    {
      "page": "b1_initial",
      "title": "Main initialization functions",
      "topics": [
        "initial.em.gbd",
        "initial.RndEM.gbd"
      ]
    },
    {
      "page": "f1_lmt_I_pv",
      "title": "Likelihood Mixture Tests with Identity Cov Matrix or Only p-values",
      "topics": [
        "lmt.I",
        "lmt.pv"
      ]
    },
    {
      "page": "c1_test",
      "title": "Likelihood ratio tests",
      "topics": [
        "lrt",
        "lrt.betaab",
        "lrt.betamean",
        "lrt2"
      ]
    },
    {
      "page": "a1_fclust",
      "title": "Main MixfMRI function",
      "topics": [
        "fclust",
        "PARAM",
        "PARAM.org",
        "set.global"
      ]
    },
    {
      "page": "11_d_control",
      "title": "Sets of controls in MixfMRI",
      "topics": [
        ".FC.CT"
      ]
    },
    {
      "page": "d1_plot",
      "title": "Main plotting function",
      "topics": [
        "plotfclust",
        "plotfclustpv",
        "plotpv",
        "plotpvlegend"
      ]
    },
    {
      "page": "d2_print",
      "title": "Print fclust related outputs",
      "topics": [
        "print.fclust"
      ]
    },
    {
      "page": "e1_simulation",
      "title": "Generate datasets for MixfMRI simulations",
      "topics": [
        "gendataset"
      ]
    },
    {
      "page": "e3_smooth",
      "title": "Generate datasets with smoothing for MixfMRI simulations",
      "topics": [
        "gcv.smooth2d"
      ]
    },
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      "page": "u1_summarized.overlap",
      "title": "Summarized Overlap",
      "topics": [
        "summarized.overlap"
      ]
    },
    {
      "page": "y1_Threshold.Bonferroni",
      "title": "Calculates Bonferroni Threshold",
      "topics": [
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      ]
    },
    {
      "page": "y4_Threshold.FDR",
      "title": "False Discovery Rate (FDR) Threshold",
      "topics": [
        "Threshold.FDR"
      ]
    },
    {
      "page": "y2_Threshold.RF",
      "title": "Random Field Theory Thersholds.",
      "topics": [
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      ]
    }
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  "_readme": "https://github.com/snoweye/mixfmri/raw/HEAD/README.md",
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      "headings": [
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        "2. Demonstrations",
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      "created": "2018-03-28 01:32:16",
      "modified": "2021-02-12 02:35:46",
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