FSReda_control
objectCreates an object of class FSReda_control
to be used with the fsreg()
function,
containing various control parameters.
FSReda_control(intercept = TRUE, init, nocheck = FALSE,
tstat = c("trad", "scal"), conflev = c(0.95, 0.99))
An object of class "FSReda_control"
which is basically a
list
with components the input arguments of
the function mapped accordingly to the corresponding Matlab function.
Indicator for constant term. Scalar. If intercept=TRUE
,
a model with constant term will be fitted (default), else,
no constant term will be included.
Search initialization, scalar. It specifies the initial subset size to
start monitoring exceedances of minimum deletion residual, if init is
not specified it set equal to: p+1
, if the sample size is smaller
than 40 or min(3*p+1,floor(0.5*(n+p+1)))
, otherwise. For example,
if init=100
, the procedure starts monitoring from step m=100
.
Check input arguments, scalar. If nocheck=TRUE
no check is performed
on matrix y
and matrix X
. Notice that y
and X
are left unchanged. In other words the additional column of ones for the
intercept is not added. As default nocheck=FALSE
.
The kind of t-statistics which have to be monitored.
tstat="trad"
implies monitoring of traditional t statistics
(out$Tols
). In this case the estimate of s2 at step m is based
on s2m (notice that s2m<<s2 when m/n is small) tstat="scal"
(default)
implies monitoring of rescaled t statistics. In this case the estimate
of s2 at step m is based on s2m/vartruncnorm(m/n) where vartruncnorm(m/n)
is the variance of the truncated normal distribution.
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.
FSDA team
Creates an object of class FSReda_control
to be used with the fsreg()
function,
containing various control parameters.
See Also as FSR_control
, MMreg_control
and LXS_control
if (FALSE) {
data(hbk, package="robustbase")
(out <- fsreg(Y~., data=hbk, method="FS", monitoring=TRUE,
control=FSReda_control(tstat="scal")))
}
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