| Type: | Package |
| Title: | Fit Repeated Linear Regressions |
| SystemRequirements: | GNU Scientific Library (GSL). Note: users should have GSL installed. |
| Version: | 1.3.0 |
| Date: | 2023-10-10 |
| Author: | Lijun Wang [aut, cre, cph] |
| Maintainer: | Lijun Wang <szcfweiya@gmail.com> |
| Description: | When fitting a set of linear regressions which have some same variables, we can separate the matrix and reduce the computation cost. This package aims to fit a set of repeated linear regressions faster. More details can be found in this blog Lijun Wang (2017) https://stats.hohoweiya.xyz/regression/2017/09/26/An-R-Package-Fit-Repeated-Linear-Regressions/. |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://github.com/szcf-weiya/fRLR, https://stats.hohoweiya.xyz/regression/2017/09/26/An-R-Package-Fit-Repeated-Linear-Regressions/ |
| Imports: | Rcpp (≥ 0.12.12) |
| LinkingTo: | Rcpp |
| RoxygenNote: | 7.2.3 |
| Encoding: | UTF-8 |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| VignetteBuilder: | knitr |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | yes |
| Packaged: | 2023-10-11 23:10:15 UTC; weiya |
| Repository: | CRAN |
| Date/Publication: | 2023-10-12 13:20:06 UTC |
Fit Repeated Linear Regressions with One Variable
Description
Fit a set of linear regressions which differ only in one variable.
Usage
frlr1(R_X, R_Y, R_COV, num_threads = -1L)
Arguments
R_X |
the observation matrix |
R_Y |
the response |
R_COV |
common variables |
num_threads |
number of threads for openmp. If it is -1 (default), it will use all possible threads. |
Value
the fitting results for each regression.
Examples
set.seed(123)
X = matrix(rnorm(50), 10, 5)
Y = rnorm(10)
COV = matrix(rnorm(40), 10, 4)
frlr1(X, Y, COV)
Fit Repeated Linear Regressions with Two Variables
Description
Fit a set of linear regressions which differ only in two variables.
Usage
frlr2(R_X, R_idx1, R_idx2, R_Y, R_COV, num_threads = -1L)
Arguments
R_X |
the observation matrix |
R_idx1 |
the first identical feature |
R_idx2 |
the second identical feature |
R_Y |
the response variable |
R_COV |
common variables |
num_threads |
number of threads for openmp. If it is -1 (default), it will use all possible threads. |
Value
the fitting results for each regression.
Examples
set.seed(123)
X = matrix(rnorm(50), 10, 5)
Y = rnorm(10)
COV = matrix(rnorm(40), 10, 4)
idx1 = c(1, 2, 3, 4, 1, 1, 1, 2, 2, 3)
idx2 = c(2, 3, 4, 5, 3, 4, 5, 4, 5, 5)
frlr2(X, idx1, idx2, Y, COV)