Package: bigReg
Type: Package
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.
        Data can be created using the data_frame() function and
        appended to the object with object$append(data); data_frame and
        data_matrix objects are available that allow the user to store
        large data on disk. The data is stored as doubles in binary
        format and any character columns are transformed to factors and
        then stored as numeric (binary) data while a look-up table is
        stored in a separate .meta_data file in the same folder. The
        data is stored in blocks and GLM regression algorithm is
        modified and carries out a MapReduce- like algorithm to fit the
        model. The functions bglm(), and summary() and bglm_predict()
        are available for creating and post-processing of models. The
        library requires Armadillo installed on your system. It
        probably won't function on windows since multi-core processing
        is done using mclapply() which forks R on Unix/Linux type
        operating systems.
License: GPL (>=2)
Depends: R (>= 3.2.0), Rcpp (>= 0.12.3), parallel, methods, stats, uuid
        (>= 0.1-2), MASS (>= 7.3-39)
LinkingTo: Rcpp, RcppArmadillo (>= 0.5.200.1.0)
OS_type: unix
Collate: 'RcppExports.R' 'data_frame.r' 'data_matrix.r' 'family.r'
        '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
RemoteRef: HEAD
RemoteSha: 73d725d2cd9c3b0bee14d14ce92852428200db69
NeedsCompilation: yes
Packaged: 2026-07-04 17:21:03 UTC; root