blb4lm: Bag of Little Bootstrap for Linear Regression
In yf-jiang/blb4RG: Bag of Little Bootstrap for Linear Model
Description
Usage
Arguments
Details
Value
Description
Bag of Little Bootstrap for Linear Regression
Usage
1
Arguments
formula
The formula for linear regression, using ~ operator
s
Number of subsamples
r
Times of resampling performed on each subsample
data
A data frame
parallel
Logical indicating whether parallel computation should be used. See 'details'.
Details
Split the training data into s parts and resampling r times for each part; then fit lm model given the formula for each resamples.
If you choose to use parallel computation, use "plan(multiprocess, workers = number of cores you want to use)" from furrr package first.
Value
A list of list of coefficients and sigma
yf-jiang/blb4RG documentation built on March 25, 2020, 1:28 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Details Value
Description
Bag of Little Bootstrap for Linear Regression
Usage
1 |
Arguments
formula |
The formula for linear regression, using ~ operator |
s |
Number of subsamples |
r |
Times of resampling performed on each subsample |
data |
A data frame |
parallel |
Logical indicating whether parallel computation should be used. See 'details'. |
Details
Split the training data into s parts and resampling r times for each part; then fit lm model given the formula for each resamples. If you choose to use parallel computation, use "plan(multiprocess, workers = number of cores you want to use)" from furrr package first.
Value
A list of list of coefficients and sigma
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.