initest_options {pense} | R Documentation |
Specify additional options for the initial estimator based on the Pena-Yohai estimator.
initest_options(keep_solutions = 5, psc_method = c("exact", "rr"), maxit = 10, maxit_pense_refinement = 5, eps = 1e-06, psc_keep = 0.5, resid_keep_method = c("proportion", "threshold"), resid_keep_prop = 0.6, resid_keep_thresh = 2, mscale_eps = 1e-08, mscale_maxit = 200)
keep_solutions |
how many initial estimates should be kept to perform full PENSE iterations? |
psc_method |
The method to use for computing the principal sensitivity components. See details for the possible choices. |
maxit |
maximum number of refinement iterations. |
maxit_pense_refinement |
maximum number of PENSE iterations to refine initial estimator. |
eps |
numeric tolerance for convergence. |
psc_keep |
proportion of observations to keep based on the PSC scores. |
resid_keep_method |
How to clean the data based on large residuals.
If |
resid_keep_prop, resid_keep_thresh |
proportion or threshold for observations to keep based on their residual. |
mscale_eps, mscale_maxit |
maximum number of iterations and numeric tolerance for the M-scale. |
Two different methods to calculate the sensitivity components are implemented:
"rr"
Approximate the PSCs by using the residuals from the
elastic net fit and the hat matrix from the ridge regression.
This method only works if alpha
< 1 or
ncol(x)
< nrow(x)
.
"exact"
Calculate the PSCs from the difference between the residuals and leave-one-out residuals from elastic net.
a checked options list.
Pena, D., & Yohai, V.. (1999). A Fast Procedure for Outlier Diagnostics in Large Regression Problems. Journal of the American Statistical Association, 94(446), 434-445. http://doi.org/10.2307/2670164
Other specifying additional options: en_options_aug_lars
,
mstep_options
, pense_options