bdlm_paral: Linear regression using MLR-MR algorithm

In BigDataStatMeth: Statistical Methods and Algorithms for Big Data

Linear regression using MLR-MR algorithm

Description

Linear regression for Big Data using MLR-MR algorithm to perform lm regression with big data : https://isglobal-brge.github.io/Master_Modelling/dealing-with-big-data-in-r.html#linear-regression-for-big-data

Usage

bdlm_paral(Y, model, blocks, threads = NULL)

Arguments

Y,	numerical matrix column with response variable
model,	numerical matrix with paired observations of the predictor variable X
blocks,	integer with number of blocks we want to split matrix if null matrix is splited in blocks as maximum of 1000 variables per block
threads,	threads (optional) only if bparal = true, number of concurrent threads in parallelization if threads is null then threads = maximum number of threads available

Value

Lineal regression coefficients

Examples

## Not run: 
    library(BigDataStatMeth)
    data(mtcars)

    Y <- mtcars$mpg
    X <- model.matrix(~ wt + cyl, data=mtcars)
    m <- 4
    res <- bdlm_paral( X, Y, m, 1)
    res

## End(Not run)

BigDataStatMeth documentation built on March 30, 2022, 1:07 a.m.