Bootstrap the regression coefficients for a robust linear regression model
Description
This function provides an easy interface and useful output to bootstrapping the regression coefficients of robust linear regression models
Usage
1 2 3 4 5 6 7 8 9 10  bootcoefs(object, R = 999, method = c("frb", "residuals", "cases"),
ncpus = NULL, cl = NULL, ...)
## S3 method for class 'complmrob'
bootcoefs(object, R = 999, method = c("frb",
"residuals", "cases"), ncpus = NULL, cl = NULL, ...)
## S3 method for class 'lmrob'
bootcoefs(object, R = 999, method = c("frb", "residuals",
"cases"), ncpus = NULL, cl = NULL, ...)

Arguments
object 
the model to bootstrap the coefficients from 
R 
the number of bootstrap replicates. 
method 
one of 
ncpus 
the number of CPUs to utilize for bootstrapping. 
cl 
a snow or parallel cluster to use for bootstrapping. 
... 
currently ignored. 
Details
The default method is to use fast and robust bootstrap as described in the paper by M. SalibianBarrera, et al. (see references). The other options are to bootstrap the residuals or to bootstrap cases (observations), but the sampling distribution of the estimates from these methods can be numerically instable and take longer to compute.
Value
A list of type bootcoefs
for which print
,
summary
and plot
methods are available
Methods (by class)

complmrob
: For robust linear regression models with compositional data 
lmrob
: For standard robust linear regression models
References
M. SalibianBarrera, S. Aelst, and G. Willems. Fast and robust bootstrap. Statistical Methods and Applications, 17(1):4171, 2008.
Examples
1 2 3 4 5 6 
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