{
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  "Package": "bigstatsr",
  "Type": "Package",
  "Title": "Statistical Tools for Filebacked Big Matrices",
  "Version": "1.6.3",
  "Date": "2025-06-30",
  "Authors@R": "c(\nperson(\"Florian\", \"Privé\", email = \"florian.prive.21@gmail.com\",\nrole = c(\"aut\", \"cre\")),\nperson(\"Michael\", \"Blum\", role = \"ths\"),\nperson(\"Hugues\", \"Aschard\", email = \"hugues.aschard@pasteur.fr\", role = \"ths\"))",
  "Description": "Easy-to-use, efficient, flexible and scalable statistical\ntools. Package bigstatsr provides and uses Filebacked Big\nMatrices via memory-mapping. It provides for instance matrix\noperations, Principal Component Analysis, sparse linear\nsupervised models, utility functions and more\n<doi:10.1093/bioinformatics/bty185>.",
  "License": "GPL-3",
  "Language": "en-US",
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  "Collate": "'AUC.R' 'FBM-attach.R' 'crochet.R' 'FBM.R' 'FBM-code256.R'\n'FBM-copy.R' 'RcppExports.R' 'SVD.R' 'apply-parallelize.R'\n'biglasso.R' 'bigstatsr-package.R' 'colstats.R'\n'crossprodSelf.R' 'mult-mat.R' 'mult-vec.R' 'pcor.R' 'plot.R'\n'predict.R' 'randomSVD.R' 'read-write.R' 'scaling.R'\n'summary.R' 'tcrossprodSelf.R' 'transpose.R' 'univLinReg.R'\n'univLogReg.R' 'utils-assert.R' 'utils.R' 'zzz.R'",
  "Repository": "https://privefl.r-universe.dev",
  "Date/Publication": "2026-06-05 05:19:45 UTC",
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  "Packaged": {
    "Date": "2026-06-05 07:32:58 UTC",
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  "Author": "Florian Privé [aut, cre],\nMichael Blum [ths],\nHugues Aschard [ths]",
  "Maintainer": "Florian Privé <florian.prive.21@gmail.com>",
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    "add_code256",
    "as_FBM",
    "as_scaling_fun",
    "asPlotlyText",
    "AUC",
    "AUCBoot",
    "big_apply",
    "big_attach",
    "big_attachExtdata",
    "big_colstats",
    "big_copy",
    "big_cor",
    "big_counts",
    "big_cprodMat",
    "big_cprodVec",
    "big_crossprodSelf",
    "big_increment",
    "big_parallelize",
    "big_prodMat",
    "big_prodVec",
    "big_randomSVD",
    "big_read",
    "big_scale",
    "big_spLinReg",
    "big_spLogReg",
    "big_SVD",
    "big_tcrossprodSelf",
    "big_transpose",
    "big_univLinReg",
    "big_univLogReg",
    "big_write",
    "block_size",
    "cols_along",
    "covar_from_df",
    "diag",
    "FBM",
    "FBM.code256",
    "get_beta",
    "nb_cores",
    "pasteLoc",
    "pcor",
    "plot_grid",
    "plus",
    "rows_along",
    "sub_bk",
    "theme_bigstatsr",
    "typeof",
    "without_downcast_warning"
  ],
  "_help": [
    {
      "page": "as_scaling_fun",
      "title": "Scaling function creator",
      "topics": [
        "as_scaling_fun"
      ]
    },
    {
      "page": "asPlotlyText",
      "title": "Plotly text",
      "topics": [
        "asPlotlyText"
      ]
    },
    {
      "page": "AUC",
      "title": "AUC",
      "topics": [
        "AUC",
        "AUCBoot"
      ]
    },
    {
      "page": "big_apply",
      "title": "Split-Apply-Combine",
      "topics": [
        "big_apply"
      ]
    },
    {
      "page": "big_colstats",
      "title": "Standard univariate statistics",
      "topics": [
        "big_colstats"
      ]
    },
    {
      "page": "big_copy",
      "title": "Copy as a Filebacked Big Matrix",
      "topics": [
        "big_copy"
      ]
    },
    {
      "page": "big_cor",
      "title": "Correlation",
      "topics": [
        "big_cor"
      ]
    },
    {
      "page": "big_counts",
      "title": "Counts for class FBM.code256",
      "topics": [
        "big_counts"
      ]
    },
    {
      "page": "big_cprodMat",
      "title": "Cross-product with a matrix",
      "topics": [
        "big_cprodMat",
        "crossprod,FBM,matrix-method",
        "crossprod,matrix,FBM-method",
        "tcrossprod,FBM,matrix-method",
        "tcrossprod,matrix,FBM-method"
      ]
    },
    {
      "page": "big_cprodVec",
      "title": "Cross-product with a vector",
      "topics": [
        "big_cprodVec"
      ]
    },
    {
      "page": "big_crossprodSelf",
      "title": "Crossprod",
      "topics": [
        "big_crossprodSelf",
        "crossprod,FBM,missing-method"
      ]
    },
    {
      "page": "big_increment",
      "title": "Increment an FBM",
      "topics": [
        "big_increment"
      ]
    },
    {
      "page": "big_parallelize",
      "title": "Split-parApply-Combine",
      "topics": [
        "big_parallelize"
      ]
    },
    {
      "page": "big_prodMat",
      "title": "Product with a matrix",
      "topics": [
        "%*%,FBM,matrix-method",
        "%*%,matrix,FBM-method",
        "big_prodMat"
      ]
    },
    {
      "page": "big_prodVec",
      "title": "Product with a vector",
      "topics": [
        "big_prodVec"
      ]
    },
    {
      "page": "big_randomSVD",
      "title": "Randomized partial SVD",
      "topics": [
        "big_randomSVD"
      ]
    },
    {
      "page": "big_read",
      "title": "Read a file as FBM",
      "topics": [
        "big_read"
      ]
    },
    {
      "page": "big_scale",
      "title": "Some scaling functions",
      "topics": [
        "big_scale"
      ]
    },
    {
      "page": "big_spLinReg",
      "title": "Sparse linear regression",
      "topics": [
        "big_spLinReg"
      ]
    },
    {
      "page": "big_spLogReg",
      "title": "Sparse logistic regression",
      "topics": [
        "big_spLogReg"
      ]
    },
    {
      "page": "big_SVD",
      "title": "Partial SVD",
      "topics": [
        "big_SVD"
      ]
    },
    {
      "page": "big_tcrossprodSelf",
      "title": "Tcrossprod",
      "topics": [
        "big_tcrossprodSelf",
        "tcrossprod,FBM,missing-method"
      ]
    },
    {
      "page": "big_transpose",
      "title": "Transpose an FBM",
      "topics": [
        "big_transpose"
      ]
    },
    {
      "page": "big_univLinReg",
      "title": "Column-wise linear regression",
      "topics": [
        "big_univLinReg"
      ]
    },
    {
      "page": "big_univLogReg",
      "title": "Column-wise logistic regression",
      "topics": [
        "big_univLogReg"
      ]
    },
    {
      "page": "big_write",
      "title": "Write an FBM to a file",
      "topics": [
        "big_write"
      ]
    },
    {
      "page": "block_size",
      "title": "Determine a correct value for the block.size parameter",
      "topics": [
        "block_size"
      ]
    },
    {
      "page": "covar_from_df",
      "title": "Numeric matrix from data frame",
      "topics": [
        "covar_from_df"
      ]
    },
    {
      "page": "FBM-class",
      "title": "Class FBM",
      "topics": [
        "as_FBM",
        "FBM",
        "FBM-class",
        "FBM_RC"
      ]
    },
    {
      "page": "FBM-methods",
      "title": "Methods for the FBM class",
      "topics": [
        "diag,FBM-method",
        "dim,FBM-method",
        "FBM-methods",
        "length,FBM-method",
        "typeof,FBM-method",
        "[,FBM,ANY,ANY,ANY-method",
        "[<-,FBM,ANY,ANY,ANY-method"
      ]
    },
    {
      "page": "FBM.code256-class",
      "title": "Class FBM.code256",
      "topics": [
        "add_code256",
        "FBM.code256",
        "FBM.code256-class",
        "FBM.code256_RC"
      ]
    },
    {
      "page": "get_beta",
      "title": "Combine sets of coefficients",
      "topics": [
        "get_beta"
      ]
    },
    {
      "page": "pasteLoc",
      "title": "Get coordinates on plot",
      "topics": [
        "pasteLoc"
      ]
    },
    {
      "page": "pcor",
      "title": "Partial correlation",
      "topics": [
        "pcor"
      ]
    },
    {
      "page": "plot.big_sp_list",
      "title": "Plot method",
      "topics": [
        "plot.big_sp_list"
      ]
    },
    {
      "page": "plot.big_SVD",
      "title": "Plot method",
      "topics": [
        "plot.big_SVD"
      ]
    },
    {
      "page": "plot.mhtest",
      "title": "Plot method",
      "topics": [
        "plot.mhtest"
      ]
    },
    {
      "page": "predict.big_sp",
      "title": "Predict method",
      "topics": [
        "predict.big_sp"
      ]
    },
    {
      "page": "predict.big_sp_list",
      "title": "Predict method",
      "topics": [
        "predict.big_sp_list"
      ]
    },
    {
      "page": "predict.big_SVD",
      "title": "Scores of PCA",
      "topics": [
        "predict.big_SVD"
      ]
    },
    {
      "page": "predict.mhtest",
      "title": "Predict method",
      "topics": [
        "predict.mhtest"
      ]
    },
    {
      "page": "sub_bk",
      "title": "Replace extension '.bk'",
      "topics": [
        "sub_bk"
      ]
    },
    {
      "page": "summary.big_sp_list",
      "title": "Summary method",
      "topics": [
        "summary.big_sp_list"
      ]
    },
    {
      "page": "theme_bigstatsr",
      "title": "Theme ggplot2",
      "topics": [
        "theme_bigstatsr"
      ]
    },
    {
      "page": "without_downcast_warning",
      "title": "Temporarily disable downcast warning",
      "topics": [
        "without_downcast_warning"
      ]
    }
  ],
  "_readme": "https://github.com/privefl/bigstatsr/raw/HEAD/README.md",
  "_rundeps": [
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    "bigparallelr",
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