MMregeda_control | R Documentation |
MMregeda_control
object
Creates an object of class MMregeda_control
to be used with the fsreg()
function,
containing various control parameters.
MMregeda_control(intercept = TRUE, InitialEst, Soptions, eff, effshape,
refsteps = 3, tol = 1e-07, conflev, nocheck = FALSE, plot = FALSE)
intercept |
Indicator for constant term. Scalar. If |
InitialEst |
Starting values of the MM-estimator, a list with the fiollowing
elements: |
Soptions |
Options to pass to Sreg, an It is necessary to add to the S options the letter S at the beginning. For example, if you want to use the optimal rho function the supplied option is 'Srhofunc','optimal'. For example, if you want to use 3000 subsets, the supplied option is 'Snsamp',3000 |
eff |
Vector defining nominal efficiency (i.e. a series of numbers
between 0.5 and 0.99). The default value is the sequence |
effshape |
Location or scale efficiency. If |
refsteps |
Number of refining iterations in each subsample (default is |
tol |
Scalar controlling tolerance in the MM loop. The default value is |
conflev |
Confidence level which is used to declare units as outliers. Usually conflev=0.95, 0.975, 0.99 (individual alpha) or conflev=1-0.05/n, 1-0.025/n, 1-0.01/n (simultaneous alpha). Default value is 0.975 |
nocheck |
Check input arguments, scalar. If |
plot |
Plot on the screen. Scalar. If |
Creates an object of class MMregeda_control
to be used with the fsreg()
function,
containing various control parameters.
An object of class "MMregeda_control"
which is basically a
list
with components the input arguments of
the function mapped accordingly to the corresponding Matlab function.
FSDA team
See Also as FSR_control
, Sreg_control
, MMreg_control
and LXS_control
## Not run:
data(hbk, package="robustbase")
(out <- fsreg(Y~., data=hbk, method="MM", monitoring=TRUE,
control=MMregeda_control(eff=seq(0.75, 0.99, 0.01))))
## End(Not run)
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