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  "Title": "Generalized Linear Models (GLM) for Large Data Sets",
  "Version": "0.1.2",
  "Date": "2016-07-23",
  "Author": "Chibisi Chima-Okereke <chibisi@active-analytics.com>",
  "Maintainer": "Chibisi Chima-Okereke <chibisi@active-analytics.com>",
  "Description": "Allows the user to carry out GLM on very large data sets.\nData can be created using the data_frame() function and\nappended to the object with object$append(data); data_frame and\ndata_matrix objects are available that allow the user to store\nlarge data on disk. The data is stored as doubles in binary\nformat and any character columns are transformed to factors and\nthen stored as numeric (binary) data while a look-up table is\nstored in a separate .meta_data file in the same folder. The\ndata is stored in blocks and GLM regression algorithm is\nmodified and carries out a MapReduce- like algorithm to fit the\nmodel. The functions bglm(), and summary() and bglm_predict()\nare available for creating and post-processing of models. The\nlibrary requires Armadillo installed on your system. It\nprobably won't function on windows since multi-core processing\nis done using mclapply() which forks R on Unix/Linux type\noperating systems.",
  "License": "GPL (>=2)",
  "OS_type": "unix",
  "Collate": "'RcppExports.R' 'data_frame.r' 'data_matrix.r' 'family.r'\n'map_reg.r'",
  "RoxygenNote": "5.0.1",
  "Repository": "https://activeanalytics.r-universe.dev",
  "Date/Publication": "2016-08-18 20:19:31 UTC",
  "RemoteUrl": "https://github.com/activeanalytics/bigreg",
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  "_tags": [],
  "_topics": [
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    "data-frame",
    "generalized-linear-models",
    "openblas",
    "cpp"
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  "_stars": 1,
  "_contributors": [
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    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/bigReg"
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  "_searchresults": 3,
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    "extra/citation.html",
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    "extra/contents.json",
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  "_realowner": "activeanalytics",
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      "date": "2016-07-25"
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    "bglm_predict",
    "binomial_",
    "blm",
    "CreateFactor",
    "data_frame",
    "data_matrix",
    "family_",
    "Gamma_",
    "gaussian_",
    "inverse.gaussian_",
    "load_data_frame",
    "load_data_matrix",
    "myIn",
    "mySeq",
    "poisson_",
    "print.bglm",
    "print.blm",
    "print.data_frame",
    "print.data_matrix",
    "print.summary.bglm",
    "print.summary.blm",
    "process_bglm_block",
    "quasi_",
    "quasibinomial_",
    "quasipoisson_",
    "r_bind",
    "read_df_block",
    "read_df_blocks",
    "read_matrix_block",
    "read_matrix_blocks",
    "readNumericVector",
    "sum_bglm_block",
    "summary.bglm",
    "summary.blm",
    "SVD",
    "write_numeric_vector",
    "writeNumericVector",
    "XWXMatrix",
    "XWXMatrixW"
  ],
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      "title": "plasma data from the HSAUR package",
      "object": "plasma",
      "file": "plasma.RData",
      "class": [
        "data.frame"
      ],
      "fields": [
        "fibrinogen",
        "globulin",
        "ESR"
      ],
      "rows": 32,
      "table": true,
      "tojson": true
    }
  ],
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    {
      "page": "asInteger",
      "title": "converts numeric vector to integer",
      "topics": [
        "asInteger"
      ]
    },
    {
      "page": "bglm",
      "title": "Function to carry out generalized linear regression on a data_frame data object",
      "topics": [
        "bglm"
      ]
    },
    {
      "page": "bglm_predict",
      "title": "predict function for bglm object",
      "topics": [
        "bglm_predict"
      ]
    },
    {
      "page": "binomial_",
      "title": "binomial family function",
      "topics": [
        "binomial_"
      ]
    },
    {
      "page": "blm",
      "title": "Function to carry out linear regression on a data_frame data object",
      "topics": [
        "blm"
      ]
    },
    {
      "page": "CreateFactor",
      "title": "creates factor from numeric vector and character vector as levels",
      "topics": [
        "CreateFactor"
      ]
    },
    {
      "page": "data_frame",
      "title": "function to create a data_frame object",
      "topics": [
        "data_frame"
      ]
    },
    {
      "page": "data_matrix",
      "title": "function to create a data_frame object",
      "topics": [
        "data_matrix"
      ]
    },
    {
      "page": "family_",
      "title": "family function",
      "topics": [
        "family_"
      ]
    },
    {
      "page": "Gamma_",
      "title": "Gamma family function",
      "topics": [
        "Gamma_"
      ]
    },
    {
      "page": "gaussian_",
      "title": "gaussian family function",
      "topics": [
        "gaussian_"
      ]
    },
    {
      "page": "inverse.gaussian_",
      "title": "inverse.gaussian family function",
      "topics": [
        "inverse.gaussian_"
      ]
    },
    {
      "page": "load_data_frame",
      "title": "function to load data_frame object",
      "topics": [
        "load_data_frame"
      ]
    },
    {
      "page": "load_data_matrix",
      "title": "function to load data_frame object",
      "topics": [
        "load_data_matrix"
      ]
    },
    {
      "page": "myIn",
      "title": "finds whether x is in y",
      "topics": [
        "myIn"
      ]
    },
    {
      "page": "mySeq",
      "title": "mySeq function to sequence integers",
      "topics": [
        "mySeq"
      ]
    },
    {
      "page": "plasma",
      "title": "plasma data from the HSAUR package",
      "topics": [
        "plasma"
      ]
    },
    {
      "page": "poisson_",
      "title": "poisson family function",
      "topics": [
        "poisson_"
      ]
    },
    {
      "page": "print.bglm",
      "title": "print function for the bglm object",
      "topics": [
        "print.bglm"
      ]
    },
    {
      "page": "print.blm",
      "title": "print function for the blm object",
      "topics": [
        "print.blm"
      ]
    },
    {
      "page": "print.data_frame",
      "title": "print function for a data_frame",
      "topics": [
        "print.data_frame"
      ]
    },
    {
      "page": "print.data_matrix",
      "title": "print function for a data_matrix",
      "topics": [
        "print.data_matrix"
      ]
    },
    {
      "page": "print.summary.bglm",
      "title": "Function to print the summary object from the bglm object",
      "topics": [
        "print.summary.bglm"
      ]
    },
    {
      "page": "print.summary.blm",
      "title": "Function to print the summary object from the blm object",
      "topics": [
        "print.summary.blm"
      ]
    },
    {
      "page": "process_bglm_block",
      "title": "Function to print the summary object from the blm object",
      "topics": [
        "process_bglm_block"
      ]
    },
    {
      "page": "quasi_",
      "title": "quasi family function",
      "topics": [
        "quasi_"
      ]
    },
    {
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      "title": "quasibinomial family function",
      "topics": [
        "quasibinomial_"
      ]
    },
    {
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      "title": "quasipoisson family function",
      "topics": [
        "quasipoisson_"
      ]
    },
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      "title": "row binding for benchmarking ...",
      "topics": [
        "r_bind"
      ]
    },
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      "topics": [
        "read_df_block"
      ]
    },
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    },
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    },
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}